@article{DBLP:journals/corr/abs-1908-02624,
  author       = {Yolanda Gil and
                  Bart Selman},
  title        = {A 20-Year Community Roadmap for Artificial Intelligence Research in
                  the {US}},
  journal      = {CoRR},
  volume       = {abs/1908.02624},
  year         = {2019},
  url          = {http://arxiv.org/abs/1908.02624},
  eprinttype    = {arXiv},
  eprint       = {1908.02624},
  timestamp    = {Sat, 23 Jan 2021 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1908-02624.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{pujara2019common,
  title={A Common Framework for Developing Table Understanding Models.},
  author={Pujara, Jay and Rajendran, Arunkumar and Ghasemi-Gol, Majid and Szekely, Pedro A},
  booktitle={ISWC Satellites},
  pages={133--136},
  year={2019}
}

@inproceedings{Tiwari2019AComparativeStudyof,
 author = {Tiwari, Abhishek  and Cassani, Raymundo and   Narayanan, Shrikanth and  Falk, Tiago},
 booktitle = {In proceedings of 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC19)},
 location = {Berlin, Germany},
 title = {A Comparative Study of Stress and Anxiety Prediction in Ecological Settings Using a Smart-shirt and a Smart-bracelet},
 year = {2019},
 month = {Jul}
}

@misc{huang_2019, 
title={A Gentle Introduction to Graph Neural Network (Basics, DeepWalk, and GraphSage)}, url={https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3}, 
publisher={Towards Data Science}, 
author={Huang, Kung-Hsiang}, 
year={2019}, 
month={Feb}}

@InProceedings{cardenas-EtAl:2019:N19-1,
  author    = {Cardenas, Ronald  and  Lin, Ying  and  Ji, Heng  and  May, Jonathan},
  title     = {A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages},
  booktitle = {Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota},
  publisher = {Association for Computational Linguistics},
  pages     = {2428--2439},
  abstract  = {Unsupervised part of speech (POS) tagging is often framed as a clustering problem, but practical taggers need to ground their clusters as well. Grounding generally requires reference labeled data, a luxury a low-resource language might not have. In this work, we describe an approach for low-resource unsupervised POS tagging that yields fully grounded output and requires no labeled training data. We find the classic method of Brown et al. (1992) clusters well in our use case and employ a decipherment-based approach to grounding. This approach presumes a sequence of cluster IDs is a `ciphertext' and seeks a POS tag-to-cluster ID mapping that will reveal the POS sequence. We show intrinsically that, despite the difficulty of the task, we obtain reasonable performance across a variety of languages. We also show extrinsically that incorporating our POS tagger into a name tagger leads to state-of-the-art tagging performance in Sinhalese and Kinyarwanda, two languages with nearly no labeled POS data available. We further demonstrate our tagger's utility by incorporating it into a true `zero-resource' variant of the MALOPA (Ammar et al., 2016) dependency parser model that removes the current reliance on multilingual resources and gold POS tags for new languages. Experiments show that including our tagger makes up much of the accuracy lost when gold POS tags are unavailable.},
  url       = {http://www.aclweb.org/anthology/N19-1252}
}

Unsupervised part of speech (POS) tagging is often framed as a clustering problem, but practical taggers need to ground their clusters as well. Grounding generally requires reference labeled data, a luxury a low-resource language might not have. In this work, we describe an approach for low-resource unsupervised POS tagging that yields fully grounded output and requires no labeled training data. We find the classic method of Brown et al. (1992) clusters well in our use case and employ a decipherment-based approach to grounding. This approach presumes a sequence of cluster IDs is a `ciphertext' and seeks a POS tag-to-cluster ID mapping that will reveal the POS sequence. We show intrinsically that, despite the difficulty of the task, we obtain reasonable performance across a variety of languages. We also show extrinsically that incorporating our POS tagger into a name tagger leads to state-of-the-art tagging performance in Sinhalese and Kinyarwanda, two languages with nearly no labeled POS data available. We further demonstrate our tagger's utility by incorporating it into a true `zero-resource' variant of the MALOPA (Ammar et al., 2016) dependency parser model that removes the current reliance on multilingual resources and gold POS tags for new languages. Experiments show that including our tagger makes up much of the accuracy lost when gold POS tags are unavailable.

@inproceedings{Schuler2019,
	abstract = {Databases are well suited to the task of describing and organizing research datasets, however, the difficulties of using database management systems effectively have resulted in their limited usage among domain scientists. Scientists operate in an environment that is changing steadily with new experimental protocols, instruments, and discoveries that impact what datasets they generate and how they describe and organize them. In order to manage datasets for a scientific application, scientists need to routinely revise their database schemas to reflect these changes. Unfortunately, evolving a database is one of the well-known and most difficult aspects of database usage. The conventional data definition and manipulation languages offer relatively low-level programming abstractions to perform complex database evolution tasks, and therefore require specialized technical skills not possessed by most domain scientists. A simplified means of expressing database evolution operations can reduce the effort of keeping the scientific database in sync with changing requirements. This paper presents a high-level, user-oriented, schema evolution framework with an algebra of specialized schema modification operators. The approach allows introduction of novel operators as motivated by new requirements and is amenable to well established optimization techniques for efficient planning and execution. We present the framework and its implementation, and we demonstrate its utility in an exemplar use case and performance evaluation.},
	address = {{New York, NY, USA}},
	author = {Schuler, Robert E. and Kessleman, Carl},
	booktitle = {Proceedings of the 31st {{International Conference}} on {{Scientific}} and {{Statistical Database Management}}},
	doi = {10.1145/3335783.3335787},
	file = {/Users/schuler/Zotero/storage/T8CSAR3I/Schuler and Kesselman - 2019 - A High-level User-oriented Framework for Database .pdf},
	isbn = {978-1-4503-6216-0},
	keywords = {Database evolution,Schema evolution,Scientific databases},
	pages = {157--168},
	publisher = {{Association for Computing Machinery}},
	series = {{{SSDBM}} '19},
	title = {A {{High-Level User-Oriented Framework}} for {{Database Evolution}}},
	year = {2019},
	bdsk-url-1 = {https://doi.org/10.1145/3335783.3335787}}

Databases are well suited to the task of describing and organizing research datasets, however, the difficulties of using database management systems effectively have resulted in their limited usage among domain scientists. Scientists operate in an environment that is changing steadily with new experimental protocols, instruments, and discoveries that impact what datasets they generate and how they describe and organize them. In order to manage datasets for a scientific application, scientists need to routinely revise their database schemas to reflect these changes. Unfortunately, evolving a database is one of the well-known and most difficult aspects of database usage. The conventional data definition and manipulation languages offer relatively low-level programming abstractions to perform complex database evolution tasks, and therefore require specialized technical skills not possessed by most domain scientists. A simplified means of expressing database evolution operations can reduce the effort of keeping the scientific database in sync with changing requirements. This paper presents a high-level, user-oriented, schema evolution framework with an algebra of specialized schema modification operators. The approach allows introduction of novel operators as motivated by new requirements and is amenable to well established optimization techniques for efficient planning and execution. We present the framework and its implementation, and we demonstrate its utility in an exemplar use case and performance evaluation.

@inproceedings{Cen2019APersonalVisualComfort,
 author = {Cen, Lingkai and Choi, Joon-Ho and Yao, Xiaomeng and Gil, Yolanda and Narayanan, Shrikanth and Pentz,  Maryann},
 booktitle = {In proceedings of 10th International Conference on Indoor Air Quality, Ventilation and Energy Conservation in Buildings (IAQVEC2019)},
 location = {Bari, Italy},
 month = {Sep},
 title = {A Personal Visual Comfort Model: Predict Individuals Visual Comfort Using Occupant Eye Pupil Size and Machine Learning},
 year = {2019}
}

@inproceedings{cen-etal-iaqvec19,
author = {Lingkai Cen and Joon-Ho Choi and Xiaomeng Yao and Yolanda Gil and Shrikanth Narayanan and Maryann Pentz},
title = {A Personal Visual Comfort Model: Predict an Individual\textquotesingle s Visual Comfort Using Occupant Eye Pupil Sizes and Machine Learning},
booktitle = {Tenth International Conference on Indoor Air Quality, Ventilation and Energy Conservation in Buildings, IOP Conference Series in Materials Science and Engineering (609)4},
address = {Bari, Italy},
year = {2019}
}

@InProceedings{	  bogol-iwsg-2019,
  Title		= {A Secure Gateway for Enabling ASIC Design Collaborations},
  Author	= {Bogol, Steve and Brenner, Paul and Brinckman, Adam and
		  Deelman, Ewa and Ferreira da Silva, Rafael and Gupta,
		  Sandeep and Nabrzyski, Jarek and Park, Soowang and Perez,
		  Damian and Rynge, Mats and Taylor, Ian and Vahi, Karan and
		  Werf, Matt Vander and Rucker Sarah and Wyngaard,
		  Sebastian},
  BookTitle	= {11th International Workshop on Science Gateways (IWSG
		  2019)},
  Year		= {2019},
  Pages		= {},
  DOI		= {},
  Note		= {Funding Acknowledgments: DARPA HR0011-16-C-0043}
}

@article{DBLP:journals/corr/abs-1909-06516,
  author    = {Mozhdeh Gheini and
               Jonathan May},
  title     = {A Universal Parent Model for Low-Resource Neural Machine Translation
               Transfer},
  journal   = {CoRR},
  volume    = {abs/1909.06516},
  year      = {2019},
  url       = {http://arxiv.org/abs/1909.06516},
  archivePrefix = {arXiv},
  eprint    = {1909.06516},
  timestamp = {Mon, 23 Sep 2019 18:07:15 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1909-06516.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{jalal2019cooperative,
  title={A cooperative machine learning approach for pedestrian navigation in indoor IoT},
  author={Jalal Abadi, Marzieh and Luceri, Luca and Hassan, Mahbub and Chou, Chun Tung and Nicoli, Monica},
  journal={Sensors},
  volume={19},
  number={21},
  pages={4609},
  year={2019},
  publisher={MDPI}
}

@article{Alex2019Amodulararchitecturefor,
 author = {Alexander, Rachel  and  Sorensen, Tanner and  Toutios, Asterios and  Narayanan, Shrikanth},
 bib2html_rescat = {span},
 doi = {https://doi.org/10.1121/1.5139413},
 journal = {J. Acoust. Soc. Am.},
 link = {http://sail.usc.edu/publications/files/Alexander-JASA2020.pdf},
 month = {dec},
 number = {6},
 pages = {4458-4471},
 title = {A modular architecture for articulatory synthesis from gestural specification},
 volume = {146},
 year = {2019}
}

@article{PendergrassBuyskeJeffEtAl2019,
	abstract = {We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one {SNP} is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the {Population Architecture using Genomics and Epidemiology} (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each {SNP} on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.},
	author = {Pendergrass, Sarah A. and Buyske, Steven and Jeff, Janina M. and Frase, Alex and Dudek, Scott and Bradford, Yuki and Ambite, Jose-Luis and Avery, Christy L. and Buzkova, Petra and Deelman, Ewa and Fesinmeyer, Megan D. and Haiman, Christopher and Heiss, Gerardo and Hindorff, Lucia A. and Hsu, Chun-Nan and Jackson, Rebecca D. and Lin, Yi and Le Marchand, Loic and Matise, Tara C. and Monroe, Kristine R. and Moreland, Larry and North, Kari E. and Park, Sungshim L. and Reiner, Alex and Wallace, Robert and Wilkens, Lynne R. and Kooperberg, Charles and Ritchie, Marylyn D. and Crawford, Dana C.},
	citation-subset = {IM},
	completed = {2020-04-06},
	country = {United States},
	doi = {10.1371/journal.pone.0226771},
	issn = {1932-6203},
	issn-linking = {1932-6203},
	issue = {12},
	journal = {PloS one},
	keywords = {African Americans, genetics; Aged; Atherosclerosis, genetics; Epidemiologic Studies; Female; Genetic Pleiotropy; Genome-Wide Association Study; Humans; Male; Metagenomics; Middle Aged; Phenomics; Polymorphism, Single Nucleotide},
	nlm-id = {101285081},
	owner = {NLM},
	pages = {e0226771},
	pii = {PONE-D-19-33442},
	pmc = {PMC6938343},
	pmid = {31891604},
	url = {https://pubmed.ncbi.nlm.nih.gov/31891604/},

	pubmodel = {Electronic-eCollection},
	pubstate = {epublish},
	revised = {2020-04-30},
	title = {A phenome-wide association study ({PheWAS}) in the {Population Architecture using Genomics and Epidemiology} ({PAGE}) study reveals potential pleiotropy in {African Americans}.},
	volume = {14},
	year = {2019},
	bdsk-url-1 = {https://pubmed.ncbi.nlm.nih.gov/31891604/},
	bdsk-url-2 = {https://doi.org/10.1371/journal.pone.0226771}}

We performed a hypothesis-generating phenome-wide association study (PheWAS) to identify and characterize cross-phenotype associations, where one SNP is associated with two or more phenotypes, between thousands of genetic variants assayed on the Metabochip and hundreds of phenotypes in 5,897 African Americans as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study. The PAGE I study was a National Human Genome Research Institute-funded collaboration of four study sites accessing diverse epidemiologic studies genotyped on the Metabochip, a custom genotyping chip that has dense coverage of regions in the genome previously associated with cardio-metabolic traits and outcomes in mostly European-descent populations. Here we focus on identifying novel phenome-genome relationships, where SNPs are associated with more than one phenotype. To do this, we performed a PheWAS, testing each SNP on the Metabochip for an association with up to 273 phenotypes in the participating PAGE I study sites. We identified 133 putative pleiotropic variants, defined as SNPs associated at an empirically derived p-value threshold of p<0.01 in two or more PAGE study sites for two or more phenotype classes. We further annotated these PheWAS-identified variants using publicly available functional data and local genetic ancestry. Amongst our novel findings is SPARC rs4958487, associated with increased glucose levels and hypertension. SPARC has been implicated in the pathogenesis of diabetes and is also known to have a potential role in fibrosis, a common consequence of multiple conditions including hypertension. The SPARC example and others highlight the potential that PheWAS approaches have in improving our understanding of complex disease architecture by identifying novel relationships between genetic variants and an array of common human phenotypes.

@InProceedings{sticca2019:ASHG,
  author = 	 {E.L. Sticca and G.M. Belbin and J. Soto and R. Shemirani and D. Nelson and  S. Gravel and J.L. Ambite and G.L. Wojcik and E.E. Kenny and C.R. Gignoux},
  title = 	 {A pipeline for large-scale simulation of population-based linkage.},
  booktitle = {Annual Meeting of the American Society of Human Genetics},
  year = 	 {2019},
  address = 	 {Houston, TX},
  note = 	 {Abstract + Poster},
}

@inproceedings{Martinez2019Asystemforthe,
 author = {Martinez, Victor and Ramakrishna, Anil and Chiu, Ming-Chang and Singla, Karan and Narayanan, Shrikanth},
 booktitle = {In proceedings of Proceedings of the 8th International Conference on Affective  Computing Intelligent Interaction},
 location = {Cambridge, UK},
 month = {September},
 title = {A system for the 2019 Sentiment, Emotion and  Cognitive State Task of DARPAs LORELEI project},
 year = {2019}
}

@article{lu2019universal,
  title={A universal measure for network traceability},
  author={Lu, Xin and Horn, Abigail L and Su, Jiahao and Jiang, Jiang},
  journal={Omega},
  volume={87},
  pages={191--204},
  year={2019},
  publisher={Elsevier}
}

@article{DBLP:journals/corr/abs-1903-00788,
  author       = {Ayush Jaiswal and
                  Yue Wu and
                  Wael AbdAlmageed and
                  Iacopo Masi and
                  Premkumar Natarajan},
  title        = {{AIRD:} Adversarial Learning Framework for Image Repurposing Detection},
  journal      = {CoRR},
  volume       = {abs/1903.00788},
  year         = {2019},
  url          = {http://arxiv.org/abs/1903.00788},
  eprinttype    = {arXiv},
  eprint       = {1903.00788},
  timestamp    = {Sat, 30 Mar 2019 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1903-00788.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@InProceedings{	  ferreiradasilva-iccs-2019,
  Author	= {Ferreira da Silva, Rafael and Orgerie, Anne-C\'{e}cile and
		  Casanova, Henri and Tanaka, Ryan and Deelman, Ewa and
		  Suter, Fr\'{e}d\'{e}ric},
  Title		= {Accurately Simulating Energy Consumption of I/O-intensive
		  Scientific Workflows},
  BookTitle	= {Computational Science -- ICCS 2019},
  Year		= {2019},
  Pages		= {138--152},
  Publisher	= {Springer International Publishing},
  DOI		= {10.1007/978-3-030-22734-0_11},
  Note		= {Funding Acknowledgments: NSF 1642335, NSF 1664162, DOE
		  DE-SC0012636}
}

@inbook{Toutios2018AdvancesInVocalTractImaging,
 address = {New York, NY},
 author = {Toutios, Asterios and Byrd, Dani and Goldstein, Louis and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 link = {},
 publisher = {Routledge London and New York},
 title = {Advances in vocal tract imaging and analysis},
 year = {2019},
 month = {Apr}
}

@article{DBLP:journals/f1000research/HornAAABBBBBFGGKLLMMOST19,
  author       = {John D. Van Horn and
                  Sumiko Abe and
                  Jos{\'{e}} Luis Ambite and
                  Teresa K. Attwood and
                  Niall Beard and
                  Louisa Bellis and
                  Avnish Bhattrai and
                  Alex A. T. Bui and
                  Gully Burns and
                  Lily Fierro and
                  Jonathan Gordon and
                  Jeffrey S. Grethe and
                  Jeana Kamdar and
                  Xiaoyu Lei and
                  Kristina Lerman and
                  Annette McGrath and
                  Nicola J. Mulder and
                  Caroline O'Driscoll and
                  Crystal Stewart and
                  Sonika Tyagi},
  title        = {Advancing the international data science workforce through shared
                  training and education},
  journal      = {F1000Research},
  volume       = {8},
  pages        = {251},
  year         = {2019},
  url          = {https://doi.org/10.12688/f1000research.18357.1},
  doi          = {10.12688/F1000RESEARCH.18357.1},
  timestamp    = {Mon, 28 Aug 2023 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/f1000research/HornAAABBBBBFGGKLLMMOST19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/mta/RiazAPCMN19,
  author       = {Sidra Riaz and
                  Zahid Ali and
                  Unsang Park and
                  Jongmoo Choi and
                  Iacopo Masi and
                  Prem Natarajan},
  title        = {Age-invariant face recognition using gender specific 3D aging modeling},
  journal      = {Multim. Tools Appl.},
  volume       = {78},
  number       = {17},
  pages        = {25163--25183},
  year         = {2019},
  url          = {https://doi.org/10.1007/s11042-019-7694-1},
  doi          = {10.1007/S11042-019-7694-1},
  timestamp    = {Mon, 11 May 2020 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/mta/RiazAPCMN19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Sharon2019AnEmpiricalStudyof,
 author = {Sharon, Rini and Narayanan, Shrikanth and Sur, Mriganka and Murthy, Hema},
 booktitle = {Proceedings of ICASSP},
 location = {Brighton, UK},
 month = {May},
 title = {An Empirical Study of Speech Processing in the Brain by Analyzing the Temporal Syllable Structure in Speech-input Induced EEG},
 year = {2019}
}

@inproceedings{Garijo:2019:III:3308557.3308711,
 author = {Garijo, Daniel and Khider, Deborah and Ratnakar, Varun and Gil, Yolanda and Deelman, Ewa and da Silva, Rafael Ferreira and Knoblock, Craig and Chiang, Yao-Yi and Pham, Minh and Pujara, Jay and Vu, Binh and Feldman, Dan and Mayani, Rajiv and Cobourn, Kelly and Duffy, Chris and Kemanian, Armen and Shu, Lele and Kumar, Vipin and Khandelwal, Ankush and Tayal, Kshitij and Peckham, Scott and Stoica, Maria and Dabrowski, Anna and Hardesty-Lewis, Daniel and Pierce, Suzanne},
 title = {An Intelligent Interface for Integrating Climate, Hydrology, Agriculture, and Socioeconomic Models},
 booktitle = {Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion},
 series = {IUI '19},
 year = {2019},
 isbn = {978-1-4503-6673-1},
 location = {Marina del Ray, California},
 pages = {111--112},
 numpages = {2},
 url = {http://doi.acm.org/10.1145/3308557.3308711},
 urlPaper = {http://usc-isi-i2.github.io/papers/daniel19-iui.pdf},
 doi = {10.1145/3308557.3308711},
 acmid = {3308711},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {environmental modeling, intelligent workflow systems, model integration, scientific discovery},
} 

@InProceedings{	  garijo-iui-2019,
  Author	= {Garijo, Daniel and Khider, Deborah and Ratnakar, Varun and
		  Gil, Yolanda and Deelman, Ewa and Ferreira da Silva, Rafael
		  and Knoblock, Craig and Chiang, Yao-Yi and Pham, Minh and
		  Pujara, Jay and Vu, Binh and Feldman, Dan and Mayani, Rajiv
		  and Cobourn, Kelly and Duffy, Chris and Kemanian, Armen and
		  Shu, Lele and Kumar, Vipin and Khandelwal, Ankush and
		  Tayal, Kshitij and Peckham, Scott and Stoica, Maria and
		  Dabrowski, Anna and Hardesty-Lewis, Daniel and Pierce,
		  Suzanne},
  Title		= {An Intelligent Interface for Integrating Climate,
		  Hydrology, Agriculture, and Socioeconomic Models},
  BookTitle	= {ACM 24th International Conference on Intelligent User
		  Interfaces (IUI'19)},
  Year		= {2019},
  Pages		= {111--112},
  DOI		= {10.1145/3308557.3308711},
  Note		= {Funding Acknowledgments: DARPA W911NF-18-1-0027}
}

@article{Albash_2019,
	doi = {10.1088/2058-9565/ab13ea},
	url = {https://doi.org/10.1088%2F2058-9565%2Fab13ea},
	year = 2019,
	month = {apr},
	publisher = {{IOP} Publishing},
	volume = {4},
	number = {2},
	pages = {02LT03},
	author = {Tameem Albash and Victor Martin-Mayor and Itay Hen},
	title = {Analog errors in Ising machines},
	journal = {Quantum Science and Technology},
	abstract = {Recent technological breakthroughs have precipitated the availability of specialized devices that promise to solve NP-Hard problems faster than standard computers. These ‘Ising Machines’ are however analog in nature and as such inevitably have implementation errors. We find that their success probability decays exponentially with problem size for a fixed error level, and we derive a sufficient scaling law for the error in order to maintain a fixed success probability. We corroborate our results with experiment and numerical simulations and discuss the practical implications of our findings.}
}

Recent technological breakthroughs have precipitated the availability of specialized devices that promise to solve NP-Hard problems faster than standard computers. These ‘Ising Machines’ are however analog in nature and as such inevitably have implementation errors. We find that their success probability decays exponentially with problem size for a fixed error level, and we derive a sufficient scaling law for the error in order to maintain a fixed success probability. We corroborate our results with experiment and numerical simulations and discuss the practical implications of our findings.

@article{npjQ,
	Abstract = {Quantum annealing has the potential to provide a speedup over classical algorithms in solving optimization problems. Just as for any other quantum device, suppressing Hamiltonian control errors will be necessary before quantum annealers can achieve speedups. Such analog control errors are known to lead to {\$}{\$}J{\$}{\$}J-chaos, wherein the probability of obtaining the optimal solution, encoded as the ground state of the intended Hamiltonian, varies widely depending on the control error. Here, we show that {\$}{\$}J{\$}{\$}J-chaos causes a catastrophic failure of quantum annealing, in that the scaling of the time-to-solution metric becomes worse than that of a deterministic (exhaustive) classical solver. We demonstrate this empirically using random Ising spin glass problems run on the two latest generations of the D-Wave quantum annealers. We then proceed to show that this doomsday scenario can be mitigated using a simple error suppression and correction scheme known as quantum annealing correction (QAC). By using QAC, the time-to-solution scaling of the same D-Wave devices is improved to below that of the classical upper bound, thus restoring hope in the speedup prospects of quantum annealing.},
	Author = {Pearson, Adam and Mishra, Anurag and Hen, Itay and Lidar, Daniel A.},
	Da = {2019/11/28},
	Date-Added = {2020-05-11 16:55:01 -0700},
	Date-Modified = {2020-05-11 16:55:01 -0700},
	Doi = {10.1038/s41534-019-0210-7},
	Id = {Pearson2019},
	Isbn = {2056-6387},
	Journal = {npj Quantum Information},
	Number = {1},
	Pages = {107},
	Title = {Analog errors in quantum annealing: doom and hope},
	Ty = {JOUR},
	Url = {https://doi.org/10.1038/s41534-019-0210-7},
	Volume = {5},
	Year = {2019},
	Bdsk-Url-1 = {https://doi.org/10.1038/s41534-019-0210-7}}

Quantum annealing has the potential to provide a speedup over classical algorithms in solving optimization problems. Just as for any other quantum device, suppressing Hamiltonian control errors will be necessary before quantum annealers can achieve speedups. Such analog control errors are known to lead to \$}{\$J\$}{\$J-chaos, wherein the probability of obtaining the optimal solution, encoded as the ground state of the intended Hamiltonian, varies widely depending on the control error. Here, we show that \$}{\$J\$}{\$J-chaos causes a catastrophic failure of quantum annealing, in that the scaling of the time-to-solution metric becomes worse than that of a deterministic (exhaustive) classical solver. We demonstrate this empirically using random Ising spin glass problems run on the two latest generations of the D-Wave quantum annealers. We then proceed to show that this doomsday scenario can be mitigated using a simple error suppression and correction scheme known as quantum annealing correction (QAC). By using QAC, the time-to-solution scaling of the same D-Wave devices is improved to below that of the classical upper bound, thus restoring hope in the speedup prospects of quantum annealing.

@article{Slutskii_2019,
	doi = {10.1088/1367-2630/ab51f9},
	url = {https://doi.org/10.1088%2F1367-2630%2Fab51f9},
	year = 2019,
	month = {nov},
	publisher = {{IOP} Publishing},
	volume = {21},
	number = {11},
	pages = {113025},
	author = {Mikhail Slutskii and Tameem Albash and Lev Barash and Itay Hen},
	title = {Analog nature of quantum adiabatic unstructured search},
	journal = {New Journal of Physics},
	abstract = {The quantum adiabatic unstructured search algorithm is one of only a handful of quantum adiabatic optimization algorithms to exhibit provable speedups over their classical counterparts. With no fault tolerance theorems to guarantee the resilience of such algorithms against errors, understanding the impact of imperfections on their performance is of both scientific and practical significance. We study the robustness of the algorithm against various types of imperfections: limited control over the interpolating schedule, Hamiltonian misspecification, and interactions with a thermal environment. We find that the unstructured search algorithm’s quadratic speedup is generally not robust to the presence of any one of the above non-idealities, and in some cases we find that it imposes unrealistic conditions on how the strength of these noise sources must scale to maintain the quadratic speedup.}
}

The quantum adiabatic unstructured search algorithm is one of only a handful of quantum adiabatic optimization algorithms to exhibit provable speedups over their classical counterparts. With no fault tolerance theorems to guarantee the resilience of such algorithms against errors, understanding the impact of imperfections on their performance is of both scientific and practical significance. We study the robustness of the algorithm against various types of imperfections: limited control over the interpolating schedule, Hamiltonian misspecification, and interactions with a thermal environment. We find that the unstructured search algorithm’s quadratic speedup is generally not robust to the presence of any one of the above non-idealities, and in some cases we find that it imposes unrealistic conditions on how the strength of these noise sources must scale to maintain the quadratic speedup.

@article{pepke2019,
	Author = {Pepke, Shirley and Nelson, William M and {Ver Steeg}, Greg},
	Date-Added = {2020-01-20 20:40:51 +0000},
	Date-Modified = {2020-01-20 20:40:51 +0000},
	Journal = {JoVE (Journal of Visualized Experiments)},
	Number = {152},
	Pages = {e60431},
	Title = {Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal},
	Year = {2019}}

@article{luceri2019analyzing,
  title={Analyzing and inferring human real-life behavior through online social networks with social influence deep learning},
  author={Luceri, Luca and Braun, Torsten and Giordano, Silvia},
  journal={Applied network science},
  volume={4},
  number={1},
  pages={1--25},
  year={2019},
  publisher={Springer}
}

@InProceedings{	  chap2019precs,
  Author	= {Chapp, Dylan and Rorabaugh, Danny and Brown, Duncan A. and
		  Deelman, Ewa and Vahi, Karan and Welch, Von and Taufer,
		  Michela},
  Title		= {Applicability Study of the PRIMAD Model to LIGO
		  Gravitational Wave Search Workflows},
  Year		= {2019},
  DOI		= {10.1145/3322790.3330591},
  BookTitle	= {Proceedings of the 2nd International Workshop on Practical
		  Reproducible Evaluation of Computer Systems (P-RECS'19)},
  Pages		= {1–6}
}

@article{li_applying_2019,
	title = {Applying {Multivariate} {Segmentation} {Methods} to {Human} {Activity} {Recognition} {From} {Wearable} {Sensors}' {Data}.},
	volume = {7},
	copyright = {(c)Kenan Li, Rima Habre, Huiyu Deng, Robert Urman, John Morrison, Frank D Gilliland, Jose Luis Ambite, Dimitris Stripelis, Yao-Yi Chiang, Yijun Lin, Alex AT Bui, Christine King, Anahita Hosseini, Eleanne Van Vliet, Majid Sarrafzadeh, Sandrah P Eckel. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 07.02.2019.},
	issn = {2291-5222 2291-5222},
	url = {https://mhealth.jmir.org/2019/2/e11201/},
	doi = {10.2196/11201},
	abstract = {BACKGROUND: Time-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accurate machine learning algorithms for human activity recognition (HAR) have been developed using data from wearable devices (eg, smartwatch and smartphone). However, many HAR algorithms depend on fixed-size sampling windows that may poorly adapt to real-world conditions in which activity bouts are of unequal duration. A small sliding window can produce noisy predictions under stable conditions, whereas a large sliding window may miss brief bursts of intense activity. OBJECTIVE: We aimed to create an HAR framework adapted to variable duration activity bouts by (1) detecting the change points of activity bouts in a multivariate time series and (2) predicting activity for each homogeneous window defined by these change points. METHODS: We applied standard fixed-width sliding windows (4-6 different sizes) or greedy Gaussian segmentation (GGS) to identify break points in filtered triaxial accelerometer and gyroscope data. After standard feature engineering, we applied an Xgboost model to predict  physical activity within each window and then converted windowed predictions to instantaneous predictions to facilitate comparison across segmentation methods. We applied these methods in 2 datasets: the human activity recognition using smartphones (HARuS) dataset where a total of 30 adults performed activities of approximately equal duration (approximately 20 seconds each) while wearing a waist-worn smartphone, and the Biomedical REAl-Time Health Evaluation for Pediatric Asthma (BREATHE) dataset where a total of 14 children performed 6 activities for approximately 10 min each while wearing a smartwatch. To mimic a real-world scenario, we generated artificial unequal activity bout durations in the BREATHE data by randomly subdividing each activity bout into 10 segments and  randomly concatenating the 60 activity bouts. Each dataset was divided into {\textasciitilde}90\%  training and {\textasciitilde}10\% holdout testing. RESULTS: In the HARuS data, GGS produced the least noisy predictions of 6 physical activities and had the second highest accuracy rate of 91.06\% (the highest accuracy rate was 91.79\% for the sliding window of size 0.8 second). In the BREATHE data, GGS again produced the least noisy predictions and had the highest accuracy rate of 79.4\% of predictions for 6 physical activities. CONCLUSIONS: In a scenario with variable duration activity bouts, GGS multivariate segmentation produced smart-sized windows with more stable predictions and a higher accuracy rate than traditional fixed-size sliding window approaches. Overall, accuracy was good in both datasets but, as expected,  it was slightly lower in the more real-world study using wrist-worn smartwatches  in children (BREATHE) than in the more tightly controlled study using waist-worn  smartphones in adults (HARuS). We implemented GGS in an offline setting, but it could be adapted for real-time prediction with streaming data.},
	language = {eng},
	number = {2},
	journal = {JMIR mHealth and uHealth},
	author = {Li, Kenan and Habre, Rima and Deng, Huiyu and Urman, Robert and Morrison, John and Gilliland, Frank D. and Ambite, Jose Luis and Stripelis, Dimitris and Chiang, Yao-Yi and Lin, Yijun and Bui, Alex At and King, Christine and Hosseini, Anahita and Vliet, Eleanne Van and Sarrafzadeh, Majid and Eckel, Sandrah P.},
	month = feb,
	year = {2019},
	pmid = {30730297},
	pmcid = {PMC6386646},
	keywords = {machine learning, physical activity, smartphone, statistical data analysis wearable devices},
	pages = {e11201},
}

BACKGROUND: Time-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accurate machine learning algorithms for human activity recognition (HAR) have been developed using data from wearable devices (eg, smartwatch and smartphone). However, many HAR algorithms depend on fixed-size sampling windows that may poorly adapt to real-world conditions in which activity bouts are of unequal duration. A small sliding window can produce noisy predictions under stable conditions, whereas a large sliding window may miss brief bursts of intense activity. OBJECTIVE: We aimed to create an HAR framework adapted to variable duration activity bouts by (1) detecting the change points of activity bouts in a multivariate time series and (2) predicting activity for each homogeneous window defined by these change points. METHODS: We applied standard fixed-width sliding windows (4-6 different sizes) or greedy Gaussian segmentation (GGS) to identify break points in filtered triaxial accelerometer and gyroscope data. After standard feature engineering, we applied an Xgboost model to predict physical activity within each window and then converted windowed predictions to instantaneous predictions to facilitate comparison across segmentation methods. We applied these methods in 2 datasets: the human activity recognition using smartphones (HARuS) dataset where a total of 30 adults performed activities of approximately equal duration (approximately 20 seconds each) while wearing a waist-worn smartphone, and the Biomedical REAl-Time Health Evaluation for Pediatric Asthma (BREATHE) dataset where a total of 14 children performed 6 activities for approximately 10 min each while wearing a smartwatch. To mimic a real-world scenario, we generated artificial unequal activity bout durations in the BREATHE data by randomly subdividing each activity bout into 10 segments and randomly concatenating the 60 activity bouts. Each dataset was divided into ~90% training and ~10% holdout testing. RESULTS: In the HARuS data, GGS produced the least noisy predictions of 6 physical activities and had the second highest accuracy rate of 91.06% (the highest accuracy rate was 91.79% for the sliding window of size 0.8 second). In the BREATHE data, GGS again produced the least noisy predictions and had the highest accuracy rate of 79.4% of predictions for 6 physical activities. CONCLUSIONS: In a scenario with variable duration activity bouts, GGS multivariate segmentation produced smart-sized windows with more stable predictions and a higher accuracy rate than traditional fixed-size sliding window approaches. Overall, accuracy was good in both datasets but, as expected, it was slightly lower in the more real-world study using wrist-worn smartwatches in children (BREATHE) than in the more tightly controlled study using waist-worn smartphones in adults (HARuS). We implemented GGS in an offline setting, but it could be adapted for real-time prediction with streaming data.

@article{Proctor2019ArticulatoryCharacterizationofEnglish,
 abstract = {Articulation of liquid consonants in onsets and codas by four speakers of General American English was examined using real-time MRI. Midsagittal tongue posture was compared for laterals and rhotics produced in each syllable margin, adjacent to 13 different vowels and diphthongs. Vowel articulation was examined in words without liquids, before each liquid, and after each liquid, to assess the coarticulatory influence of each segment on the others. Overall, nuclear vocalic postures were more influenced by coda rhotics than onset rhotics or laterals in either syllable margin. Laterals exhibited greater temporal and spatial independence between coronal and dorsal gestures. Rhotics were produced with a variety of speaker-specific postures, but were united by a greater degree of coarticulatory resistance to vowel context, patterns consistent with greater coarticulatory influence on adjacent vowels, and less allophonic variation across syllable positions than laterals.},
 author = {Proctor, Michael and Walker, Rachel and Smith, Caitlin and Szalay, Tunde and Goldstein, Louis and Narayanan, Shrikanth},
 doi = {https://doi.org/10.1016/j.wocn.2019.100921},
 issn = {0095-4470},
 journal = {J. Phonetics},
 keywords = {Liquid consonant, Rhotic, Lateral, Coarticulation, Syllable structure},
 link = {http://sail.usc.edu/publications/files/proctor_jphon-2019.pdf},
 pages = {100921},
 title = {Articulatory Characterization of English Liquid-Final Rimes},
 url = {http://www.sciencedirect.com/science/article/pii/S0095447018300457},
 volume = {77},
 year = {2019},
 month = {Aug}
}

Articulation of liquid consonants in onsets and codas by four speakers of General American English was examined using real-time MRI. Midsagittal tongue posture was compared for laterals and rhotics produced in each syllable margin, adjacent to 13 different vowels and diphthongs. Vowel articulation was examined in words without liquids, before each liquid, and after each liquid, to assess the coarticulatory influence of each segment on the others. Overall, nuclear vocalic postures were more influenced by coda rhotics than onset rhotics or laterals in either syllable margin. Laterals exhibited greater temporal and spatial independence between coronal and dorsal gestures. Rhotics were produced with a variety of speaker-specific postures, but were united by a greater degree of coarticulatory resistance to vowel context, patterns consistent with greater coarticulatory influence on adjacent vowels, and less allophonic variation across syllable positions than laterals.

@article{Park2019Auto-TuningSpectralClusteringfor,
 author = {Park, Tae Jin and Han, Kyu and Kumar, Manoj and Narayanan, Shrikanth},
 doi = {10.1109/LSP.2019.2961071},
 journal = {IEEE Signal Processing Letters},
 title = {Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap},
 year = {2019},
 month = {Mar}
}

@inproceedings{aistats2019,
	Author = {Shuyang Gao and Robert Brekelmans and Greg {Ver Steeg} and Aram Galstyan},
	Booktitle = {Proceedings of the 22nd International Conference on AI and Statistics (AISTATS)},
	Date-Added = {2019-01-24 17:43:17 +0000},
	Date-Modified = {2019-01-24 17:44:47 +0000},
	Title = {Auto-encoding Correlation Explanation},
	Year = {2019}}

@inproceedings{gao2019auto,
  title={Auto-encoding total correlation explanation},
  author={Gao, Shuyang and Brekelmans, Rob and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
  pages={1157--1166},
  year={2019},
  organization={PMLR}
}

@article{uhl2019automated,
  title={Automated extraction of human settlement patterns from historical topographic map series using weakly supervised convolutional neural networks},
  author={Uhl, Johannes H and Leyk, Stefan and Chiang, Yao-Yi and Duan, Weiwei and Knoblock, Craig A},
  journal={IEEE Access},
  year={2019},
  publisher={IEEE},
  urlLink={https://ieeexplore.ieee.org/document/8946322},
  urlPaper={http://usc-isi-i2.github.io/papers/uhl19-ieee.pdf}
}

@InProceedings{mayani2019a:ASHG,
  author = 	 {R. Mayani and K. Vahi and J.L. Ambite and S. Sharma and M. Azaro and S. Wilson and B. Ruocco and G. Davis and M. Romanella and L. Brzustowicz and E. Deelman and Y. Arens},
  title = 	 {Automated processing of phenotypic data submissions},
  booktitle = {Annual Meeting of the American Society of Human Genetics},
  year = 	 {2019},
  address = 	 {Houston, TX},
  note = 	 {Abstract + Poster},
}

@inproceedings{shi2019automatic,
  title={Automatic Adaptation to Sensor Replacements},
  author={Shi, Yuan and Kumar, TK Satish and Knoblock, Craig A},
  booktitle={The Thirty-Second International Flairs Conference},
  year={2019}
}

@article{duan2019automatic,
  title={Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning},
  author={Duan, Weiwei and Chiang, Yao-Yi and Leyk, Stefan and Uhl, Johannes H and Knoblock, Craig A},
  journal={International Journal of Geographical Information Science},
  pages={1--26},
  year={2019},
  publisher={Taylor \& Francis}
}

@article{ALOBAID2019100472,
	title        = {Automating ontology engineering support activities with OnToology},
	author       = {Ahmad Alobaid and Daniel Garijo and María Poveda-Villalón and Idafen Santana-Perez and Alba Fernández-Izquierdo and Oscar Corcho},
	year         = 2019,
	journal      = {Journal of Web Semantics},
	volume       = 57,
	pages        = 100472,
	doi          = {10.1016/j.websem.2018.09.003},
	issn         = {1570-8268},
	url          = {https://dgarijo.com/papers/JWSsupporting.pdf},
	keywords     = {Ontology engineering, Ontology evaluation, Ontology documentation, Ontology publication},
	abstract     = {Due to the increasing uptake of semantic technologies, ontologies are now part of a good number of information systems. As a result, software development teams that have to combine ontology engineering activities with software development practices are facing several challenges, since these two areas have evolved, in general, separately. In this paper we present OnToology, an approach to manage ontology engineering support activities (i.e., documentation, evaluation, releasing and versioning). OnToology is a web-based application that builds on top of Git-based environments and integrates existing semantic web technologies. We have validated OnToology against a set of representative requirements for ontology development support activities in distributed environments, and report on a survey of the system to assess its usefulness and usability.}
}

Due to the increasing uptake of semantic technologies, ontologies are now part of a good number of information systems. As a result, software development teams that have to combine ontology engineering activities with software development practices are facing several challenges, since these two areas have evolved, in general, separately. In this paper we present OnToology, an approach to manage ontology engineering support activities (i.e., documentation, evaluation, releasing and versioning). OnToology is a web-based application that builds on top of Git-based environments and integrates existing semantic web technologies. We have validated OnToology against a set of representative requirements for ontology development support activities in distributed environments, and report on a survey of the system to assess its usefulness and usability.

@article{ambite2019bd2k,
  title={BD2K Training Coordinating Center's ERuDIte: the Educational Resource Discovery Index for Data Science},
  author={Ambite, Jose Luis and Fierro, Lily and Gordon, Jonathan and Burns, Gully and Geigl, Florian and Lerman, Kristina and Van Horn, John D},
  journal={IEEE Transactions on Emerging Topics in Computing},
  year={2019},
  publisher={IEEE}
}

@Article{ambite2019:tetc-DONTCITEUPDATE2021,
  author = 	 {Jos\'{e} Luis Ambite and Lily Fierro and Jonathan Gordon and Gully A. Burns and Florian Geigl and Kristina Lerman and John D. Van Horn},
  title = 	 {{BD2K Training Coordinating Center’s ERuDIte: the Educational Resource Discovery Index for Data Science}},
  journal = 	 {IEEE Transactions on Emerging Topics in Computing},
  year = 	 {2019},
  DOI = {10.1109/TETC.2019.2903466},
  note = {10.1109/TETC.2019.2903466},
  publisher = {IEEE Computer Society},
  address = {Los Alamitos, CA, USA},
  month = {Jan}
}

@InBook{mythodologies-2019,
  author =    {Joseph A. Dane and Jonathan May},
  title =        {Begging The Question: Critical Reasoning in Chaucer Studies, Book History, and Humanistic Inquiry},
  chapter =      {III.3: Evidence and Artificial Intelligence},
  publisher =    {Marymount Institute Press},
  year =         2019,
  number =    {II},
  series =    {Mythodologies},
  pages =     {295--208}}

@article{ghazarian2019better,
  title={Better automatic evaluation of open-domain dialogue systems with contextualized embeddings},
  author={Ghazarian, Sarik and Wei, Johnny Tian-Zheng and Galstyan, Aram and Peng, Nanyun},
  journal={arXiv preprint arXiv:1904.10635},
  year={2019}
}

@misc{bd2k-erudite,
  author = {{BD2K-TCC}},
  title = {{Big Data to Knowledge (BD2K) Training Coordinating Center (TCC) Educational Resource Discovery Index (ERuDIte) as Linked Data}},
  howpublished = {https://doi.org/10.5281/zenodo.2553415},
  year = {2019}, 
  note = {[Online; accessed 16-August-2021]}
}

@article{Mathew2019BiomedicalNE,
  title={Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping},
  author={Joel Mathew and Shobeir Fakhraei and J. Ambite},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.00282}
}

@inproceedings{khachatrian2019biorelex,
  title={Biorelex 1.0: Biological relation extraction benchmark},
  author={Khachatrian, Hrant and Nersisyan, Lilit and Hambardzumyan, Karen and Galstyan, Tigran and Hakobyan, Anna and Arakelyan, Arsen and Rzhetsky, Andrey and Galstyan, Aram},
  booktitle={Proceedings of the 18th BioNLP Workshop and Shared Task},
  pages={176--190},
  year={2019}
}

@inproceedings{Mundnich2019BluetoothbasedIndoorLocalization,
 author = {Mundnich, Karel and Girault, Benjamin and Narayanan, Shrikanth},
 booktitle = {Proceedings of ICASSP},
 link = {http://sail.usc.edu/publications/files/Mundnich-ICASSP2019.pdf},
 location = {Brighton, UK},
 month = {May},
 title = {Bluetooth based Indoor Localization using Triplet Embeddings},
 year = {2019}
}

@inproceedings{chevalier2019bootkeeper,
  title={BootKeeper: Validating Software Integrity Properties on Boot Firmware Images},
  author={Chevalier, Ronny and Cristalli, Stefano and Hauser, Christophe and Shoshitaishvili, Yan and Wang, Ruoyu and Kruegel, Christopher and Vigna, Giovanni and Bruschi, Danilo and Lanzi, Andrea},
  booktitle={Proceedings of the Ninth ACM Conference on Data and Application Security and Privacy},
  pages={315--325},
  year={2019}
}

@InProceedings{8902700,
  author = {A. Tiwari and S. Narayanan and T. H. Falk},
  booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)},
  title = {Breathing Rate Complexity Features for “In-the-Wild” Stress and Anxiety Measurement},
  year = {2019},
  pages = {1-5},
  abstract = {Features extracted from respiratory activity signals have been shown to carry information about mental states such as anxiety and mental stress. Such findings, however, are based on studies conducted mostly in controlled laboratory environments with artificially-induced psychological responses. While this assures that high quality data are collected, the amount of data is limited and the transferability of the findings to more ecologically-appropriate natural settings (i.e., “in-the-wild”) remains unknown. In this paper, we propose new non-linear complexity measures computed from four different respiration activity time series (i.e., inter-breath interval, inhale-to-exhale ratio, inhale/exhale amplitude envelope, and interbreath difference) and show their discriminatory power for anxiety and stress monitoring in the workplace. The new features are tested on a dataset collected from 200 hospital workers (nurses and staff) during their normal work shifts. The proposed features are shown to be complementary to conventional measures of breathing rate and depth.},
  keywords = {diseases;feature extraction;medical signal processing;patient care;pneumodynamics;psychology;time series;artificially-induced psychological responses;ecologically-appropriate natural settings;nonlinear complexity measures;inter-breath interval;stress monitoring;respiratory activity signals;mental states;breathing rate complexity features;anxiety measurement;respiration activity time series;in-the-wild stress;feature extraction;Feature extraction;Stress;Benchmark testing;Biomedical measurement;Stress measurement;Time series analysis;Entropy},
  doi = {10.23919/EUSIPCO.2019.8902700},
  issn = {2076-1465},
  month = {Sep.},
}

Features extracted from respiratory activity signals have been shown to carry information about mental states such as anxiety and mental stress. Such findings, however, are based on studies conducted mostly in controlled laboratory environments with artificially-induced psychological responses. While this assures that high quality data are collected, the amount of data is limited and the transferability of the findings to more ecologically-appropriate natural settings (i.e., “in-the-wild”) remains unknown. In this paper, we propose new non-linear complexity measures computed from four different respiration activity time series (i.e., inter-breath interval, inhale-to-exhale ratio, inhale/exhale amplitude envelope, and interbreath difference) and show their discriminatory power for anxiety and stress monitoring in the workplace. The new features are tested on a dataset collected from 200 hospital workers (nurses and staff) during their normal work shifts. The proposed features are shown to be complementary to conventional measures of breathing rate and depth.

@inproceedings{ferreiradasilva2019escience,
    title = {Bridging Concepts and Practice in eScience via Simulation-driven Engineering},
    author = {Ferreira da Silva, Rafael and Casanova, Henri and Tanaka, Ryan and Suter, Frederic},
    booktitle = {Workshop on Bridging from Concepts to Data and Computation for eScience (BC2DC'19), 15th International Conference on eScience (eScience)},
    year = {2019},
    pages = {609--614},
    doi = {10.1109/eScience.2019.00084},
    note = {Funding Acknowledgements: NSF 1642335, NSF 1923539}
}

@INPROCEEDINGS{Chiang2019-yx,
  title     = "{Building Explainable Predictive Analytics for Location-Dependent
               Time-Series Data}",
  booktitle = "{Proceedings of the 2019 IEEE First International Conference on
               Cognitive Machine Intelligence (CogMI)}",
  author    = "Chiang, Y Y and Lin, Y and Franklin, M and Eckel, S P and
               Ambite, J L and Ku, W",
  pages     = "202--209",
  month     =  dec,
  year      =  2019,
  url       = "http://dx.doi.org/10.1109/CogMI48466.2019.00037",
  url-file      = "papers/Chiang-et-al.-2019-Building-Explainable-Predictive-Analytics-for-Location-Dependent-Time-Series-Data.pdf",
  doi       = "10.1109/CogMI48466.2019.00037"
}

@article{burns2019building,
  title={Building deep learning models for evidence classification from the open access biomedical literature},
  author={Burns, Gully A and Li, Xiangci and Peng, Nanyun},
  journal={Database},
  volume={2019},
  year={2019},
  publisher={Narnia}
}

@InProceedings{Moura19b,
	author = 	"Giovane C. M. Moura and John Heidemann and
 Ricardo de O. Schmidt and Wes Hardaker",
	title = 	"Cache Me If You Can: Effects of {DNS} {Time-to-Live}",
        booktitle =     "Proceedings of the " # "ACM Internet Measurement Conference",
        year =          2019,
	sortdate = "2019-10-31",
	project = "ant, lacanic, divoice, paaddos, nipet, ddidd",
	jsubject = "network_security",
        pages =      "to appear",
        month =      oct,
        address =    "Amsterdam, the Netherlands",
        publisher =  "ACM",
        jlocation =   "johnh: pafile",
	keywords = 	"anycast, dns, ttl, ddos, root ddos",
	doi = "https://doi.org/10.1145/3355369.3355568",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Moura19b.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Moura19b.pdf",
	blogurl = "https://ant.isi.edu/blog/?p=1355",
	dataurl =	"https://ant.isi.edu/datasets/dns/#Moura19b_data",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "DNS depends on extensive caching for good performance, and every DNS
zone owner must set \emph{Time-to-Live} (TTL) values to control their DNS
caching.  Today there is relatively little guidance backed by research
about how to set TTLs, and operators must balance conflicting demands
of caching against agility of configuration.  
Exactly how TTL value choices affect operational
networks is quite challenging to understand due to interactions across the
distributed DNS service, where resolvers receive TTLs in different ways
(answers and hints), TTLs are specified in multiple places (zones and
their parent's glue), and while DNS resolution must be security-aware.
This paper provides the first careful evaluation of how these multiple,
interacting factors affect the effective cache lifetimes of DNS records,
and provides recommendations for how to configure DNS TTLs based on
our findings.  We provide recommendations in TTL choice for different
situations, and for where they must be configured.  We show that longer
TTLs have significant promise in reducing latency, reducing it from
183ms to 28.7ms for one country-code TLD.",
}

DNS depends on extensive caching for good performance, and every DNS zone owner must set \emphTime-to-Live (TTL) values to control their DNS caching. Today there is relatively little guidance backed by research about how to set TTLs, and operators must balance conflicting demands of caching against agility of configuration. Exactly how TTL value choices affect operational networks is quite challenging to understand due to interactions across the distributed DNS service, where resolvers receive TTLs in different ways (answers and hints), TTLs are specified in multiple places (zones and their parent's glue), and while DNS resolution must be security-aware. This paper provides the first careful evaluation of how these multiple, interacting factors affect the effective cache lifetimes of DNS records, and provides recommendations for how to configure DNS TTLs based on our findings. We provide recommendations in TTL choice for different situations, and for where they must be configured. We show that longer TTLs have significant promise in reducing latency, reducing it from 183ms to 28.7ms for one country-code TLD.

@inproceedings{Moura:2019:CMY:3355369.3355568,
 author = {Moura, Giovane C. M. and Heidemann, John and Schmidt, Ricardo de O. and Hardaker, Wes},
 title = {Cache Me If You Can: Effects of DNS Time-to-Live},
 booktitle = {Proceedings of the Internet Measurement Conference},
 series = {IMC '19},
 year = {2019},
 isbn = {978-1-4503-6948-0},
 location = {Amsterdam, Netherlands},
 pages = {101--115},
 numpages = {15},
 url = {http://doi.acm.org/10.1145/3355369.3355568},
 pdfurl = {https://www.isi.edu/~hardaker/papers/2019-10-cache-me-ttls.pdf},
 doi = {10.1145/3355369.3355568},
 acmid = {3355568},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {DNS, caching, recursive DNS servers},
 ISIArea="NET",
}

@TechReport{Moura19a,
	author = 	"Giovane C. M. Moura and John Heidemann and
        		Ricardo de O. Schmidt and Wes Hardaker",
	title = 	"Cache Me If You Can: Effects of {DNS} {Time-to-Live} (extended)",
	institution = 	"USC/Information Sciences Institute",
	year = 		2019,
	sortdate = "2018-07-16",
	number = 	"ISI-TR-734b",
	note = "Released May 2018, updated Sept.~2019",
	project = "ant, lacanic, divoice, paaddos, nipet, ddidd",
	jsubject = "network_security",
	month = 	jul,
	jlocation = 	"johnh: pafile",
	keywords = 	"anycast, dns, ttl, ddos, root ddos",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Moura19a.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Moura19a.pdf",
	xxxblogurl = "https://ant.isi.edu/blog/?p=1192",
	otherurl = "ftp://ftp.isi.edu/isi-pubs/tr-734.pdf",
	dataurl =	"https://ant.isi.edu/datasets/dns/#Moura19a_data",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "
DNS depends on extensive caching for good performance, and every DNS
zone owner must set Time-to-Live (TTL) values to control their
DNS caching.  Today there is relatively little guidance backed by
research about how to set TTLs, and operators must balance conflicting
demands of caching against agility of configuration.  Exactly how TTL
value choices affect operational networks is quite challenging to
understand for several reasons:  DNS is a distributed service, DNS
resolution is security-sensitive, and resolvers require multiple types
of information as they traverse the DNS hierarchy.  These complications
mean there are multiple frequently interacting, places TTLs can be
specified.  This paper provides the first careful evaluation of how
these factors affect the effective cache lifetimes of DNS records, and
provides recommendations for how to configure DNS TTLs based on our
findings.  We provide recommendations in TTL choice for different
situations, and for where they must be configured.  We show that longer
TTLs have significant promise, reducing median latency from 183ms to
28.7ms for one country-code TLD.
",
}

DNS depends on extensive caching for good performance, and every DNS zone owner must set Time-to-Live (TTL) values to control their DNS caching. Today there is relatively little guidance backed by research about how to set TTLs, and operators must balance conflicting demands of caching against agility of configuration. Exactly how TTL value choices affect operational networks is quite challenging to understand for several reasons: DNS is a distributed service, DNS resolution is security-sensitive, and resolvers require multiple types of information as they traverse the DNS hierarchy. These complications mean there are multiple frequently interacting, places TTLs can be specified. This paper provides the first careful evaluation of how these factors affect the effective cache lifetimes of DNS records, and provides recommendations for how to configure DNS TTLs based on our findings. We provide recommendations in TTL choice for different situations, and for where they must be configured. We show that longer TTLs have significant promise, reducing median latency from 183ms to 28.7ms for one country-code TLD.

@article{Turalska2019,
  title = {Cascading failures in scale-free interdependent networks},
  author = {Turalska, Malgorzata and Burghardt, Keith and Rohden, Martin and Swami, Ananthram and D'Souza, Raissa M.},
  journal = {Phys. Rev. E},
  volume = {99},
  issue = {3},
  pages = {032308},
  numpages = {9},
  year = {2019},
  month = {Mar},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.99.032308},
  url = {https://link.aps.org/doi/10.1103/PhysRevE.99.032308}
}

@InProceedings{	  thomas-escience-2019,
  Title		= {Characterization of In Situ and In Transit Analytics of
		  Molecular Dynamics Simulations for Next-generation
		  Supercomputers},
  Author	= {Thomas, Stephen and Wyatt, Michael and Do, Tu Mai Anh and
		  Pottier, Lo\"ic and Ferreira da Silva, Rafael and
		  Weinstein, Harel and Cuendet, Michel A. and Estrada, Trilce
		  and Deelman, Ewa and Taufer, Michela},
  BookTitle	= {15th International Conference on eScience (eScience)},
  Year		= {2019},
  Pages		= {188--198},
  DOI		= {10.1109/eScience.2019.00027},
  Note		= {Funding Acknowledgments: NSF 1741040}
}

@article{DBLP:journals/corr/abs-1903-00156,
  author       = {Nazgol Tavabi and
                  Nathan Bartley and
                  Andr{\'{e}}s Abeliuk and
                  Sandeep Soni and
                  Emilio Ferrara and
                  Kristina Lerman},
  title        = {Characterizing Activity on the Deep and Dark Web},
  journal      = {CoRR},
  volume       = {abs/1903.00156},
  year         = {2019},
  url          = {http://arxiv.org/abs/1903.00156},
  eprinttype    = {arXiv},
  eprint       = {1903.00156},
  timestamp    = {Sat, 30 Mar 2019 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1903-00156.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{DBLP:journals/snam/BadawyALF19,
  author       = {Adam Badawy and
                  Aseel Addawood and
                  Kristina Lerman and
                  Emilio Ferrara},
  title        = {Characterizing the 2016 Russian {IRA} influence campaign},
  journal      = {Soc. Netw. Anal. Min.},
  volume       = {9},
  number       = {1},
  pages        = {31:1--31:11},
  year         = {2019},
  url          = {https://doi.org/10.1007/s13278-019-0578-6},
  doi          = {10.1007/S13278-019-0578-6},
  timestamp    = {Wed, 07 Dec 2022 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/journals/snam/BadawyALF19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{zhu_climate_2019,
	title = {Climate models can correctly simulate the continuum of global-average temperature variability},
	volume = {116},
	copyright = {All rights reserved},
	number = {18},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Zhu, Feng and Emile-Geay, Julien and McKay, Nicholas P. and Hakim, Gregory J. and Khider, Deborah and Ault, Toby R. and Steig, Eric J. and Dee, Sylvia and Kirchner, James W.},
	year = {2019},
	note = {ISBN: 0027-8424
Publisher: National Acad Sciences},
	pages = {8728--8733},
}

@inproceedings{DBLP:conf/semweb/KejriwalS19,
  author    = {Mayank Kejriwal and
               Pedro A. Szekely},
  editor    = {Mari Carmen Su{\'{a}}rez{-}Figueroa and
               Gong Cheng and
               Anna Lisa Gentile and
               Christophe Gu{\'{e}}ret and
               C. Maria Keet and
               Abraham Bernstein},
  title     = {Co-LOD: Continuous Space Linked Open Data},
  booktitle = {Proceedings of the {ISWC} 2019 Satellite Tracks (Posters {\&} Demonstrations,
               Industry, and Outrageous Ideas) co-located with 18th International
               Semantic Web Conference {(ISWC} 2019), Auckland, New Zealand, October
               26-30, 2019},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2456},
  pages     = {333--337},
  publisher = {CEUR-WS.org},
  year      = {2019},
  url       = {http://ceur-ws.org/Vol-2456/paper94.pdf},
  timestamp = {Tue, 07 Sep 2021 14:10:34 +0200},
  biburl    = {https://dblp.org/rec/conf/semweb/KejriwalS19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@INPROCEEDINGS{8831193,
  author={Imes, Connor and Zhang, Huazhe and Zhao, Kevin and Hoffmann, Henry},
  booktitle={2019 IEEE International Conference on Autonomic Computing (ICAC)},
  title={CoPPer: Soft Real-Time Application Performance Using Hardware Power Capping},
  year={2019},
  volume={},
  number={},
  pages={31-41},
  abstract={Dynamic voltage and frequency scaling (DVFS) has been the cornerstone of innumerable software approaches to meeting application timing requirements with minimal energy. However, recent trends in technology-e.g., moving voltage converters on chip-favor hardware control of DVFS, as hardware can both react faster to external events and perform fine-grained power management across a device. We respond to these trends with CoPPer, which instead uses hardware power capping to meet application performance requirements with high energy efficiency. We find that meeting performance requirements with power capping is more challenging than using DVFS because the relationship between power and performance is non-linear and has diminishing returns at high power values. CoPPer overcomes these difficulties by using adaptive control to approximate non-linearities and a novel gain limit to avoid over-allocating power when it is no longer beneficial. We evaluate CoPPer with 20 parallel applications and compare it to both a classic linear DVFS controller and to a sophisticated control-theoretic, model-driven software DVFS manager. CoPPer provides all the functionality of the sophisticated DVFS-based approach, without requiring a user-specified model or time-consuming, exhaustive application/system pre-characterization. Compared to DVFS, CoPPer's gain limit reduces energy by 6% on average and by 12% for memory-bound applications. For high performance requirements, the energy savings are even greater: 8% on average and 18% for memory-bound applications.},
  keywords={energy conservation;multiprocessing systems;power aware computing;soft real-time application performance;hardware power capping;application timing requirements;minimal energy;voltage converters;chip-favor hardware control;fine-grained power management;adaptive control;model-driven software DVFS manager;sophisticated DVFS-based approach;memory-bound applications;dynamic voltage and frequency scaling;energy efficiency;parallel applications;linear DVFS controller;CoPPer;Copper;Software;Hardware;Timing;Power demand;Computational modeling;Market research;performance;power cap;rapl;control theory;dvfs;self aware systems;adaptive control},
  doi={10.1109/ICAC.2019.00015},
  ISSN={2474-0756},
  month={June},
  ISIArea = {CAS}
}

Dynamic voltage and frequency scaling (DVFS) has been the cornerstone of innumerable software approaches to meeting application timing requirements with minimal energy. However, recent trends in technology-e.g., moving voltage converters on chip-favor hardware control of DVFS, as hardware can both react faster to external events and perform fine-grained power management across a device. We respond to these trends with CoPPer, which instead uses hardware power capping to meet application performance requirements with high energy efficiency. We find that meeting performance requirements with power capping is more challenging than using DVFS because the relationship between power and performance is non-linear and has diminishing returns at high power values. CoPPer overcomes these difficulties by using adaptive control to approximate non-linearities and a novel gain limit to avoid over-allocating power when it is no longer beneficial. We evaluate CoPPer with 20 parallel applications and compare it to both a classic linear DVFS controller and to a sophisticated control-theoretic, model-driven software DVFS manager. CoPPer provides all the functionality of the sophisticated DVFS-based approach, without requiring a user-specified model or time-consuming, exhaustive application/system pre-characterization. Compared to DVFS, CoPPer's gain limit reduces energy by 6% on average and by 12% for memory-bound applications. For high performance requirements, the energy savings are even greater: 8% on average and 18% for memory-bound applications.

@conference {RN849,
	title = {Collaborating to leverage R\&E network infrastructures between Africa, Brazil, and the U.S.},
	booktitle = {UbuntuNet-Connect 2019},
	year = {2019},
	month = {2019},
	type = {Conference Paper},
	address = {Antananarivo, Madagascar},
	url = {https://urldefense.com/v3/__https://repository.ubuntunet.net/handle/10.20374/271__;!!FjuHKAHQs5udqho!OrfqNEjI8IYnpYEY3Wc7S4oSY6Kf82MHM8jGAJar7qa8MoXzNwtTTC2HiJsVSREP5YicoFyGz7HN7A$ },
	author = {Heidi Morgan and Julio Ibarra and Jeronimo Bezerra and Lopez, Luis Fernandez and Vasilka Chergarova and Donald A. Cox and Michael Stanton and Hazin, Aluizio and Lotz, Len and Mammen, Siju}
}

@article{muric2019collaboration,
  title={Collaboration Drives Individual Productivity},
  author={Muri{\'c}, Goran and Abeliuk, Andres and Lerman, Kristina and Ferrara, Emilio},
  journal={Proceedings of the ACM on Human-Computer Interaction},
  volume={3},
  number={CSCW},
  pages={1--24},
  year={2019},
  publisher={ACM New York, NY, USA}
}

@article{DBLP:journals/corr/abs-1911-11787,
  author       = {Goran Muric and
                  Andr{\'{e}}s Abeliuk and
                  Kristina Lerman and
                  Emilio Ferrara},
  title        = {Collaboration Drives Individual Productivity},
  journal      = {CoRR},
  volume       = {abs/1911.11787},
  year         = {2019},
  url          = {http://arxiv.org/abs/1911.11787},
  eprinttype    = {arXiv},
  eprint       = {1911.11787},
  timestamp    = {Sun, 02 Oct 2022 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1911-11787.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@Article{	  brinckman-fgcs-2018,
  Title		= {Collaborative Circuit Designs using the CRAFT Repository},
  Author	= {Brinckman, Adam and Deelman, Ewa and Gupta, Sandeep and
		  Nabrzyski, Jarek and Park, Soowang and Ferreira da Silva,
		  Rafael and Taylor, Ian J. and Vahi, Karan},
  Journal	= {Future Generation Computer Systems},
  Volume	= {94},
  Number	= {},
  Pages		= {841--853},
  Year		= {2019},
  DOI		= {10.1016/j.future.2018.01.018},
  Note		= {Funding Acknowledgments: DARPA HR0011-16-C-0043}
}

@inproceedings{embar:akbc19ws,
    author = "Embar, Varun and Pujara, Jay and Getoor, Lise",
    bib_url = "/pubs/bib/embar-akbc19ws.bib",
    booktitle = "AKBC Workshop on Federated KBs and the Open Knowledge Network",
    pdf_url = "/pubs/2019/embar-akbc19ws/embar-akbc19ws.pdf",
    sec = "ws",
    title = "Collective Alignment of Large-scale Ontologies",
    year = "2019"
}

@inprcoeedings{Yin2019ComprehensibleCT,
  title={Comprehensible Context-driven Text Game Playing},
  author={Xusen Yin and Jonathan May},
  booktitle={Proc. 2019 IEEE Conference on Games (CoG)},
  year={2019},
  month=August,
  pages={1-8}
}

@article{datta2019computational,
  title={Computational requirements for real-time ptychographic image reconstruction},
  author={Datta, Kaushik and Rittenbach, Andrew and Kang, Dong-In and Walters, John Paul