@article{hussein_comprehensive_2009,
	title = {A Comprehensive Evaluation Framework and a Comparative Study for Human Detectors},
	volume = {10},
	rights = {All rights reserved},
	issn = {1524-9050},
	doi = {10.1109/TITS.2009.2026670},
	abstract = {We introduce a framework for evaluating human detectors that considers the practical application of a detector on a full image using multisize sliding-window scanning. We produce detection error tradeoff ({DET}) curves relating the miss detection rate and the false-alarm rate computed by deploying the detector on cropped windows and whole images, using, in the latter, either image resize or feature resize. Plots for cascade classifiers are generated based on confidence scores instead of on variation of the number of layers. To assess a method's overall performance on a given test, we use the average log miss rate ({ALMR}) as an aggregate performance score. To analyze the significance of the obtained results, we conduct 10-fold cross-validation experiments. We applied our evaluation framework to two state-of-the-art cascade-based detectors on the standard {INRIA} person dataset and a local dataset of near-infrared images. We used our evaluation framework to study the differences between the two detectors on the two datasets with different evaluation methods. Our results show the utility of our framework. They also suggest that the descriptors used to represent features and the training window size are more important in predicting the detection performance than the nature of the imaging process, and that the choice between resizing images or features can have serious consequences.},
	pages = {417--427},
	number = {3},
	journaltitle = {{IEEE} Transactions on Intelligent Transportation Systems},
	author = {Hussein, M. and Porikli, F. and Davis, L.},
	date = {2009-09},
	year = {2009},
	keywords = {Aggregates, average log miss rate, Cascade, cascade classifier, comprehensive evaluation framework, cropped window, {DET} curve, detection error tradeoff, evaluation, false-alarm rate, feature resize, Histograms, histograms of oriented gradients ({HOGs}), human detection, human detector, Humans, image classification, image resize, Infrared detectors, infrared imaging, {INRIA} person dataset, Intelligent transportation systems, Intelligent vehicles, Laboratories, miss detection rate, multisize sliding-window scanning, near infrared, near-infrared image, object detection, Optical imaging, region covariance, Testing, Vehicle detection},
	file = {IEEE Xplore Abstract Record:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\EUYURI2J\\5169850.html:text/html}
}

We introduce a framework for evaluating human detectors that considers the practical application of a detector on a full image using multisize sliding-window scanning. We produce detection error tradeoff (DET) curves relating the miss detection rate and the false-alarm rate computed by deploying the detector on cropped windows and whole images, using, in the latter, either image resize or feature resize. Plots for cascade classifiers are generated based on confidence scores instead of on variation of the number of layers. To assess a method's overall performance on a given test, we use the average log miss rate (ALMR) as an aggregate performance score. To analyze the significance of the obtained results, we conduct 10-fold cross-validation experiments. We applied our evaluation framework to two state-of-the-art cascade-based detectors on the standard INRIA person dataset and a local dataset of near-infrared images. We used our evaluation framework to study the differences between the two detectors on the two datasets with different evaluation methods. Our results show the utility of our framework. They also suggest that the descriptors used to represent features and the training window size are more important in predicting the detection performance than the nature of the imaging process, and that the choice between resizing images or features can have serious consequences.

@article{mendon2009a,
	author = {Ashwin Mendon and Andrew G. Schmidt and Ron Sass},
	journal = {International Journal of Reconfigurable Computing},
	publisher = {Hindawi Publishing Corporation},
	title = {A Hardware Filesystem Implementation with Multi-Disk Support},
	year = {2009}}

@inproceedings{kim09_interspeech,
 address = {Brighton, UK},
 author = {Kim, Jangwon and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {emotion},
 booktitle = {Proceedings of InterSpeech},
 keyword = {EMOTION, SPAN},
 link = {http://sail.usc.edu/publications/files/KimInterSpeech2009.pdf},
 month = {Sep},
 title = {A detailed study of word-position effects on emotion expression in speech},
 year = {2009}
}

@inproceedings{proc_shiva:divideconquerwebapp:icme09,
 address = {Cancun, Mexico},
 author = {Sundaram, Shiva and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Multimedia Expo (ICME)},
 doi = {https://doi.org/10.1109/icme.2009.5202535},
 link = {http://sail.usc.edu/publications/files/SundaramICME2009.pdf},
 month = {Jun},
 pages = {466-469},
 title = {A divide-and-conquer approach to latent perceptual indexing of audio for large web 2.0 applications},
 year = {2009}
}

@proceedings {7348,
	title = {A learning and collaboration platform based on SAGE},
	journal = {14th Western Canadian Conference on Computing Education (WCCCE 2009)},
	year = {2009},
	address = {Vancouver, Canada},
	author = {J. Delgado and M. Joselli and S. Stanzani and S. M. Sadjadi and E. Clua and H. Alvarez}
}

@inproceedings{Shah2009Alow-complexitydynamicface-voice,
 address = {San Diego, California},
 author = {Shah, Dhaval and Han, Kyu Jeong and Narayanan, Shrikanth S.},
 bib2html_rescat = {mica},
 booktitle = {Proceedings of the IEEE International Symposium on Multimedia (ISM)},
 doi = {10.1109/ISM.2009.78},
 link = {http://sail.usc.edu/publications/files/shahism2009.pdf},
 month = {Dec},
 title = {A low-complexity dynamic face-voice feature fusion approach to multimodal person recognition},
 year = {2009}
}

@inproceedings{chiang2009:ICDAR,
	author = 	"Yao-Yi Chiang and Craig A. Knoblock",
 	title = 	"A method for automatically extracting road layers from raster maps",
	year = 	"2009",
	booktitle ="Proceedings of the Tenth International Conference on Document Analysis and Recognition",
	urlPresentation= "http://usc-isi-i2.github.io/slides/chiang09-icdar-poster.pdf",
	urlPaper= "http://usc-isi-i2.github.io/papers/chiang09-icdar.pdf",
       	Keywords = {"Map Extraction"}

	}
	
	

@InProceedings{matise2009:ASHG,
  author = {T. C. Matise and J. L. Ambite and S. A. Cole and D. C. Crawford and C. A. Haiman and C. Kooperberg and L. Le Marchand and T. A. Manolio and K. E. North and U. Peters and M. D. Ritchie and L. A. Hindorff and J. L. Haines and {for PAGE}},
  title = {A new {PAGE} in understanding complex traits: study design for analysis of Population Architecture using Genomics and Epidemiology (abstract 1781)},
  booktitle = {59th Annual Meeting of The American Society of Human Genetics},
  year = 	 {2009},
  address = 	 {Honolulu, HI},
  note = {Abstract + Poster}
}

@article{reuter_new_2009,
	title = {A new perspective on the hydroclimate variability in northern {South} {America} during the {Little} {Ice} {Age}},
	volume = {36},
	url = {https://github.com/khider/khider.github.io/blob/master/papers/reuter2009.pdf},
	doi = {10.1029/2009GL041051},
	number = {21},
	journal = {Geophysical Research Letters},
	author = {Reuter, Justin and Stott, Lowell and Khider, Deborah and Sinha, Ashish and Cheng, Hai and Edwards, R Lawrence},
	year = {2009},
}

@inproceedings{gerosa09_wocci,
 address = {Cambridge, MA},
 author = {Gerosa, Matteo and Giuliani, Diego and Narayanan, Shrikanth S. and Potamianos, Alexandros},
 booktitle = {Proceedings of the Workshop on Child, Computer and Interaction},
 doi = {10.1145/1640377.1640384},
 keyword = {childrens speech analysis, childrens speech recognition, spoken dialogue},
 link = {http://sail.usc.edu/publications/files/gerosawocci2009.pdf},
 month = {Nov},
 title = {A review of ASR technologies for childrens speech},
 year = {2009}
}

@inproceedings{proc_samuel:harmonystructure:icassp09,
 address = {Taipei, Taiwan},
 author = {Kim, Samuel and Georgiou, Panayiotis and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {10.1109/ICASSP.2009.4959995},
 link = {http://sail.usc.edu/publications/files/kimicassp2009[1].pdf},
 month = {Apr},
 pages = {1961-1964},
 title = {A robust harmony structure modeling scheme for classical music opus identification},
 year = {2009}
}

@inproceedings{DBLP:conf/iui/GrothG09,
  author       = {Paul T. Groth and
                  Yolanda Gil},
  editor       = {Cristina Conati and
                  Mathias Bauer and
                  Nuria Oliver and
                  Daniel S. Weld},
  title        = {A scientific workflow construction command line},
  booktitle    = {Proceedings of the 14th International Conference on Intelligent User
                  Interfaces, {IUI} 2009, Sanibel Island, Florida, USA, February 8-11,
                  2009},
  pages        = {445--450},
  publisher    = {{ACM}},
  year         = {2009},
  url          = {https://doi.org/10.1145/1502650.1502716},
  doi          = {10.1145/1502650.1502716},
  timestamp    = {Tue, 16 Aug 2022 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/iui/GrothG09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Chu2009Asemi-supervisedlearningapproach,
 address = {Taipei, Taiwan},
 author = {Chu, Selina and Narayanan, Shrikanth S. and Kuo, C.-C. Jay},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {10.1109/ICASSP.2009.4959912},
 link = {http://sail.usc.edu/publications/files/chuicassp2009.pdf},
 month = {Apr},
 pages = {1629-1632},
 title = {A semi-supervised learning approach to online audio background detection},
 year = {2009}
}

@inproceedings{schmidt2009a,
	author = {Andrew G. Schmidt and William V. Kritikos and Rahul R. Sharma and Ron Sass},
	booktitle = {Proceedings of the 17th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM{\textquoteright}09)},
	publisher = {IEEE Computer Society},
	title = {AIREN: A Novel Integration of On-Chip and Off-Chip FPGA Networks},
	year = {2009}}

@inproceedings{proc_yoon:mrivocaltract:icassp09,
 address = {Taipei, Taiwan},
 author = {Kim, Yoon-Chul and Narayanan, Shrikanth S. and Nayak, Krishna S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {10.1109/ICASSP.2009.4959602},
 link = {http://sail.usc.edu/publications/files/kimicassp2009[2].pdf},
 month = {Apr},
 pages = {389-392},
 title = {Accelerated 3D MRI of vocal tract shaping using compressed sensing and parallel imaging},
 year = {2009}
}

@article{Kim2009Accelerated3Dupperairway,
 author = {Kim, Yoon-Chul and Narayanan, Shrikanth S. and Nayak, Krishna S.},
 bib2html_rescat = {},
 doi = {10.1002/mrm.21953},
 journal = {Magnetic Resonance in Medicine},
 link = {http://sail.usc.edu/publications/files/KimMRM2009.pdf},
 month = {Jun},
 number = {6},
 pages = {1434-1440},
 title = {Accelerated 3D upper airway MRI using compressed sensing},
 volume = {61},
 year = {2009}
}

@inproceedings{Venugopal2009Accelerati,
	author = {Venugopalan, Vivek and Patterson, Cameron and Shinpaugh, Kevin},
	booktitle = {{Symposium on Application Accelerators in High-Performance Computing (SAAHPC)}},
	date-added = {2020-01-15 12:02:05 -0500},
	date-modified = {2020-01-15 12:02:05 -0500},
	keywords = {particle image velocimetry, GPGPU, FPGA cluster computing},
	month = jul,
	title = {{Accelerating Particle Image Velocimetry Using Hybrid Architectures}},
	year = {2009},
	Bdsk-File-1 = {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}}

@article{mirkovic2009accurately,
  title={Accurately measuring denial of service in simulation and testbed experiments},
  author={Mirkovic, Jelena and Hussain, Alefiya and Fahmy, Sonia and Reiher, Peter and Thomas, Roshan K},
  journal={IEEE Transactions on Dependable and Secure Computing},
  volume={6},
  number={2},
  pages={81--95},
  year={2009},
  publisher={IEEE}
}

@inproceedings{Kim2009Acoustictopicmodelfor,
 address = {New Paltz, New York},
 author = {Kim, Samuel and Sundaram, Shiva and Narayanan, Shrikanth S.},
 bib2html_rescat = {speechlinks},
 booktitle = {Proceedings of the Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},
 doi = {10.1109/ASPAA.2009.5346483},
 link = {http://sail.usc.edu/publications/files/kimwaspaa2009.pdf},
 month = {Oct},
 title = {Acoustic topic model for audio information retrieval},
 year = {2009}
}

@Article{	  lee2009adaptive,
  Author	= {Kevin Lee and Norman W. Paton and Rizos Sakellariou and
		  Ewa Deelman and Alvaro A. A. Fernandes and Gaurang Mehta},
  URL		= {http://pegasus.isi.edu/publications/2009/CCPE-2009.pdf},
  Title		= {Adaptive Workflow Processing and Execution in Pegasus},
  Journal	= {Concurrency and Computation: Practice and Experience},
  Volume	= {21},
  Number	= {16},
  Pages		= {1965-1981},
  Year		= {2009}
}

@article{hussein_algorithmic_2009,
	title = {Algorithmic issues in visual object recognition},
	rights = {All rights reserved},
	url = {http://drum.lib.umd.edu/handle/1903/9960},
	abstract = {This thesis is divided into two parts covering two aspects of 
 
research in the area of visual object recognition. 
 
Part I is about human detection in still images. Human 
 
detection is a challenging computer vision task due to the wide 
 
variability in human visual appearances and body poses. In this 
 
part, we present several enhancements to human detection 
 
algorithms. First, we present an extension to the integral 
 
images framework to allow for constant time computation of 
 
non-uniformly weighted summations over rectangular regions 
 
using a bundle of integral images. Such computational element 
 
is commonly used in constructing gradient-based feature 
 
descriptors, which are the most successful in shape-based human 
 
detection. Second, we introduce deformable features as an 
 
alternative to the conventional static features used in 
 
classifiers based on boosted ensembles. Deformable features can 
 
enhance the accuracy of human detection by adapting to pose 
 
changes that can be described as translations of body features. 
 
Third, we present a comprehensive evaluation framework for 
 
cascade-based human detectors. The presented framework 
 
facilitates comparison between cascade-based detection 
 
algorithms, provides a confidence measure for result, and 
 
deploys a practical evaluation scenario. 
 
Part {II} explores the possibilities of enhancing the speed of 
 
core algorithms used in visual object recognition using the 
 
computing capabilities of Graphics Processing Units ({GPUs}). 
 
First, we present an implementation of Graph Cut on {GPUs}, which 
 
achieves up to 4x speedup against compared to a {CPU} 
 
implementation. The Graph Cut algorithm has many applications 
 
related to visual object recognition such as segmentation and 
 
3D point matching. Second, we present an efficient sparse 
 
approximation of kernel matrices for {GPUs} that can 
 
significantly speed up kernel based learning algorithms, which 
 
are widely used in object detection and recognition. We present 
 
an implementation of the Affinity Propagation clustering 
 
algorithm based on this representation, which is about 6 times 
 
faster than another {GPU} implementation based on a conventional 
 
sparse matrix representation.},
	author = {Hussein, Mohamed Elsayed Ahmed},
	urldate = {2019-05-01},
	year = {2009},
	langid = {english},
	file = {Full Text PDF:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\HS8EQ9WQ\\Hussein - 2009 - Algorithmic issues in visual object recognition.pdf:application/pdf;Snapshot:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\NTJX8NPJ\\9960.html:text/html}
}

This thesis is divided into two parts covering two aspects of research in the area of visual object recognition. Part I is about human detection in still images. Human detection is a challenging computer vision task due to the wide variability in human visual appearances and body poses. In this part, we present several enhancements to human detection algorithms. First, we present an extension to the integral images framework to allow for constant time computation of non-uniformly weighted summations over rectangular regions using a bundle of integral images. Such computational element is commonly used in constructing gradient-based feature descriptors, which are the most successful in shape-based human detection. Second, we introduce deformable features as an alternative to the conventional static features used in classifiers based on boosted ensembles. Deformable features can enhance the accuracy of human detection by adapting to pose changes that can be described as translations of body features. Third, we present a comprehensive evaluation framework for cascade-based human detectors. The presented framework facilitates comparison between cascade-based detection algorithms, provides a confidence measure for result, and deploys a practical evaluation scenario. Part II explores the possibilities of enhancing the speed of core algorithms used in visual object recognition using the computing capabilities of Graphics Processing Units (GPUs). First, we present an implementation of Graph Cut on GPUs, which achieves up to 4x speedup against compared to a CPU implementation. The Graph Cut algorithm has many applications related to visual object recognition such as segmentation and 3D point matching. Second, we present an efficient sparse approximation of kernel matrices for GPUs that can significantly speed up kernel based learning algorithms, which are widely used in object detection and recognition. We present an implementation of the Affinity Propagation clustering algorithm based on this representation, which is about 6 times faster than another GPU implementation based on a conventional sparse matrix representation.

@inproceedings{chiang2009:grec,
	author = 	"Yao-Yi Chiang and Craig A. Knoblock",
 	title = 	"An Approach to Automatic Road Vectorization of Raster Maps",
	booktitle ="Proceedings of the 8th IAPR International Workshop on Graphics RECognition (GREC'09)",
	year = 	"2009",
	urlPaper= "http://usc-isi-i2.github.io/papers/chiang09-grec.pdf",
	Keywords = {"Map Extraction"}
	}
	
		

@inproceedings{tepperman09_interspeech_2,
 address = {Brighton, UK},
 author = {Tepperman, Joseph and Bresch, Erik and Kim, Yoon-Chul and Lee, Sungbok and Goldstein, Louis and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 booktitle = {Proceedings of InterSpeech},
 doi = {10.1121/1.4784612},
 link = {http://sail.usc.edu/publications/files/TeppermanInterSpeech2009[1].pdf},
 month = {Sep},
 pages = {700-703},
 title = {An Articulatory Analysis of Phonological Transfer Using Real-time MRI},
 year = {2009}
}

@InProceedings{	  kumar2009optimization,
  Author	= {Vijay S. Kumar and P. Sadayappan and Gaurang Mehta and
		  Karan Vahi and Ewa Deelman and Varun Ratnakar and Jihie Kim
		  and Yolanda Gil and Mary W. Hall and Tahsin M. Kurç and
		  Joel H. Saltz},
  URL		= {http://pegasus.isi.edu/publications/2009/hpdc153-kumar.pdf},
  Title		= {An Integrated Framework for Performance-based Optimization
		  of Scientific Workflows},
  BookTitle	= {Conference on High Performance and Distributed Computing
		  (HPDC)},
  Year		= {2009}
}

@inproceedings{proc_tsuneo:articulatorystrokes:icassp09,
 address = {Taipei, Taiwan},
 author = {Kato, Tsuneo and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {https://doi.org/10.1109/icassp.2009.4960628},
 link = {http://sail.usc.edu/publications/files/KatoICASSP2009.pdf},
 month = {Apr},
 pages = {4493-4496},
 title = {An analysis of articulatory-acoustic data based on articulatory strokes},
 year = {2009}
}

@inproceedings{Lammert2009Anarticulatorystudyof,
 address = {Portland, Oregon},
 author = {Lammert, Adam and Bresch, Erik and Byrd, Dani and Goldstein, Louis and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 booktitle = {Proceedings of the Meeting of the Acoustical Society of America},
 doi = {10.1121/1.4783736},
 link = {http://sail.usc.edu/publications/files/lammertmasa2009[poster].pdf},
 month = {May},
 title = {An articulatory study of lexicalized and epenthetic schwa using real time magnetic resonance imaging},
 year = {2009}
}

@article{Sethy2009Aniterativerelativeentropy,
 author = {Sethy, Abhinav and Georgiou, Panayiotis and Ramabhadran, Bhuvana and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {10.1109/TASL.2008.2006654},
 journal = {IEEE Transactions on Audio, Speech, and Language Processing},
 link = {http://sail.usc.edu/publications/files/SethyTASLP2009.pdf},
 month = {Jan},
 number = {1},
 pages = {13-23},
 title = {An iterative relative entropy minimization based data selection approach for n-gram model adaptation},
 volume = {17},
 year = {2009}
}

@article{Busso2009Analysisofemotionallysalient,
 author = {Busso, Carlos and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 doi = {https://doi.org/10.1109/tasl.2008.2009578},
 journal = {IEEE Transactions on Audio, Speech, and Language Processing},
 link = {http://sail.usc.edu/publications/files/BussoTASLP2009.pdf},
 month = {May},
 number = {4},
 pages = {582-596},
 title = {Analysis of emotionally salient aspects of fundamental frequency for emotion detection},
 volume = {17},
 year = {2009}
}

@article{Ramanarayanan2009Analysisofpausingbehavior,
 author = {Ramanarayanan, Vikram and Bresch, Erik and Byrd, Dani and Goldstein, Louis and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 doi = {10.1121/1.3213452},
 journal = {Journal of the Acoustical Society of America Express Letters},
 link = {http://sail.usc.edu/publications/files/ramanarayananjasa2009.pdf},
 month = {Oct},
 number = {5},
 pages = {EL160-EL165},
 title = {Analysis of pausing behavior in spontaneous speech using real-time magnetic resonance imaging of articulation},
 volume = {126},
 year = {2009}
}

@inproceedings{DBLP:conf/services/GrothG09,
  author       = {Paul Groth and
                  Yolanda Gil},
  title        = {Analyzing the Gap between Workflows and their Natural Language Descriptions},
  booktitle    = {2009 {IEEE} Congress on Services, Part I, {SERVICES} {I} 2009, Los
                  Angeles, CA, USA, July 6-10, 2009},
  pages        = {299--305},
  publisher    = {{IEEE} Computer Society},
  year         = {2009},
  url          = {https://doi.org/10.1109/SERVICES-I.2009.55},
  doi          = {10.1109/SERVICES-I.2009.55},
  timestamp    = {Fri, 24 Mar 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/services/GrothG09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{hussein_approximate_2009,
	location = {New York, {NY}, {USA}},
	title = {Approximate Kernel Matrix Computation on {GPUs} Forlarge Scale Learning Applications},
	rights = {All rights reserved},
	isbn = {978-1-60558-498-0},
	url = {http://doi.acm.org/10.1145/1542275.1542355},
	doi = {10.1145/1542275.1542355},
	series = {{ICS} '09},
	abstract = {Kernel-based learning methods require quadratic space and time complexities to compute the kernel matrix. These complexities limit the applicability of kernel methods to large scale problems with millions of data points. In this paper, we introduce a novel representation of kernel matrices on Graphics Processing Units ({GPU}). The novel representation exploits the sparseness of the kernel matrix to address the space complexity problem. It also respects the guidelines for memory access on {GPUs}, which are critical for good performance, to address the time complexity problem. Our representation utilizes the locality preserving properties of space filling curves to obtain a band approximation of the kernel matrix. To prove the validity of the representation, we use Affinity Propagation, an unsupervised clustering algorithm, as an example of kernel methods. Experimental results show a 40x speedup of {AP} using our representation without degradation in clustering performance.},
	pages = {511--512},
	booktitle = {Proceedings of the 23rd International Conference on Supercomputing},
	publisher = {{ACM}},
	author = {Hussein, Mohamed E. and Abd-Almageed, Wael},
	urldate = {2019-05-01},
	year = {2009},
	note = {event-place: Yorktown Heights, {NY}, {USA}},
	keywords = {affinity propagation, gpu, kernel methods, space filling curves, sparse matrices},
	file = {ACM Full Text PDF:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\C6XCZ2V9\\Hussein and Abd-Almageed - 2009 - Approximate Kernel Matrix Computation on GPUs Forl.pdf:application/pdf}
}

Kernel-based learning methods require quadratic space and time complexities to compute the kernel matrix. These complexities limit the applicability of kernel methods to large scale problems with millions of data points. In this paper, we introduce a novel representation of kernel matrices on Graphics Processing Units (GPU). The novel representation exploits the sparseness of the kernel matrix to address the space complexity problem. It also respects the guidelines for memory access on GPUs, which are critical for good performance, to address the time complexity problem. Our representation utilizes the locality preserving properties of space filling curves to obtain a band approximation of the kernel matrix. To prove the validity of the representation, we use Affinity Propagation, an unsupervised clustering algorithm, as an example of kernel methods. Experimental results show a 40x speedup of AP using our representation without degradation in clustering performance.

@article{Proctor09,
 author = {Proctor, Michael I. and Goldstein, Louis and Byrd, Dani and Bresch, Erik and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 doi = {10.1121/1.4783732},
 journal = {Journal of the Acoustical Society of America},
 link = {http://sail.usc.edu/publications/files/proctor09_ASAportland_2aSC08.pdf},
 number = {4},
 pages = {2568-2568},
 title = {Articulatory comparison of Tamil liquids and stops using real-time Magnetic Resonance Imaging.},
 volume = {125},
 month = {May},
 year = {2009}
}

@article{Price2009Assessmentofemergingreading,
 author = {Price, Patti and Tepperman, Joseph and Iseli, Markus and Duong, Thao and Black, Matthew P. and Wang, Shizhen and Boscardin, Christy Kim and Heritage, Margaret and Pearson, P. David and Narayanan, Shrikanth S. and Alwan, Abeer},
 bib2html_rescat = {},
 doi = {https://doi.org/10.1016/j.specom.2009.05.001},
 journal = {Speech Communication},
 link = {http://sail.usc.edu/publications/files/PriceSpCom2009.pdf},
 month = {Oct},
 number = {10},
 pages = {968-984},
 title = {Assessment of emerging reading skills in young native speakers and language learners},
 volume = {51},
 year = {2009}
}

@inproceedings{Kim2009Audiosceneunderstandingusing,
 address = {Whistler, Canada},
 author = {Kim, Samuel and Sundaram, Shiva and Georgiou, Panayiotis and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of the Neural Information Processing Systems (NIPS) Workshop},
 link = {http://sail.usc.edu/publications/files/kimnips2009.pdf},
 month = {Dec},
 title = {Audio scene understanding using topic models},
 year = {2009}
}

@article{Yildirim2009Automaticdetectionofdisfluency,
 author = {Yildirim, Serdar and Narayanan, Shrikanth S.},
 doi = {10.1109/TASL.2008.2006728},
 journal = {IEEE Transactions on Audio, Speech, and Language Processing},
 keyword = {disfluency detection, feature selection, information fusion, spoken language processing, spontaneous children speech},
 link = {http://sail.usc.edu/publications/files/yildirim_tasl_2009.pdf},
 month = {Jan},
 number = {1},
 pages = {2-12},
 title = {Automatic detection of disfluency boundaries in spontaneous speech of children using audio-visual information},
 volume = {17},
 year = {2009}
}

@inproceedings{proc_matt:autopronunciation:icassp09,
 address = {Taipei, Taiwan},
 author = {Black, Matthew P. and Tepperman, Joseph and Kazemzadeh, Abe and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {https://doi.org/10.1109/icassp.2009.4960720},
 link = {http://sail.usc.edu/publications/files/BlackICASSP2009.pdf},
 month = {Apr},
 title = {Automatic pronunciation verification of English letter-names for early literacy assessment of preliterate children},
 year = {2009}
}

@INPROCEEDINGS{Ambite09iswc,
  AUTHOR =       {Jose-Luis Ambite and Sirish Darbha and Aman Goel and Craig A. Knoblock and Kristina Lerman and Rahul Parundekar and Thomas A. Russ},
  TITLE =        {Automatically Constructing Semantic Web Services from Online Sources},
  BOOKTITLE =    {Proceedings of 8th International Semantic Web Conference},
  YEAR =         {2009},
    month={October},
  urlPaper={http://www.isi.edu/integration/papers/ambite09-iswc.pdf},
  keywords =     {semantic-modeling},
}

@inproceedings{tepperman09_interspeech,
 address = {Brighton, UK},
 author = {Tepperman, Joseph and Goldstein, Louis and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 booktitle = {Proceedings of InterSpeech},
 doi = {},
 link = {http://sail.usc.edu/publications/files/TeppermanInterSpeech2009[2].pdf},
 month = {Sep},
 title = {Automatically rating pronunciation through articulatory phonology},
 year = {2009}
}

@inproceedings{chiang09:acmgis,
	Author = {Yao-Yi Chiang and Craig A. Knoblock},
	Booktitle = {GIS '09: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems},
	Title = {Classification of Raster Maps for Automatic Feature Extraction},
	Year = {2009},
	isbn = {978-1-60558-649-6}, 
	pages = {138--147}, 
	location = {Seattle, Washington}, 
	doi = {http://doi.acm.org/10.1145/1653771.1653793}, 
	publisher = {ACM}, 
	address = {New York, NY, USA},
         urlPresentation= "http://usc-isi-i2.github.io/slides/chiang09-acmgis-slides.pdf",
	urlPaper= "http://usc-isi-i2.github.io/papers/chiang09-acmgis.pdf",
       	Keywords = {"Map Extraction"}
	}

@article{Ghosh2009Closuredurationanalysisof,
 author = {Ghosh, Prasanta Kumar and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {https://doi.org/10.1121/1.3141876},
 journal = {Journal of the Acoustical Society of America},
 link = {http://sail.usc.edu/publications/files/GhoshJASA2009.pdf},
 month = {Jul},
 number = {1},
 pages = {EL1-EL7},
 title = {Closure duration analysis of incomplete stop consonants due to stop-stop interaction},
 volume = {126},
 year = {2009}
}

@INPROCEEDINGS{Allahverdyan2009NIPS,
  author={Armen Allahverdyan and Aram Galstyan and Greg {Ver Steeg} },
  title={Clustering with prior information},
  BOOKTITLE =    {NIPS workshop: Clustering: Science or Art? Towards Principled Approaches},
  volume={},
  number={},
  pages={},
  urlpaper={http://www.isi.edu/~galstyan/papers/clustering-NIPS.pdf},
  year={2009},
  keywords =     {semi-supervised clustering}
}

@article{Sridhar2009Combininglexicalsyntacticand,
 author = {Sridhar, Vivek Kumar Rangarajan and Bangalore, Srinivas and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {10.1016/j.csl.2008.12.001},
 journal = {Computer Speech and Language},
 link = {http://sail.usc.edu/publications/files/RangarajanCSL2009.pdf},
 month = {Oct},
 number = {4},
 pages = {407-422},
 publisher = {Elsevier},
 title = {Combining lexical, syntactic and prosodic cues for improved online dialog act tagging},
 volume = {23},
 year = {2009}
}

@article{kissel2009comparative,
  title={Comparative Evaluation of Spoofing Defenses},
  author={Kissel, Ezra and Mirkovic, J},
  journal={Proceedings of IEEE Transactions on Dependable and Secure Computing},
  pages={218--232},
  year={2009}
}

@inproceedings{Black2009Comparisonofchild-humanand,
 address = {Cambridge, MA},
 author = {Black, Matthew P. and Chang, Jeannette and Chang, Jonathan and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the Workshop on Child, Computer and Interaction},
 doi = {10.1145/1640377.1640379},
 link = {http://sail.usc.edu/publications/files/blackwocci2009.pdf},
 month = {Nov},
 title = {Comparison of child-human and child-computer interactions based on manual annotations},
 year = {2009}
}

@inproceedings{nava09_interspeech,
 address = {Brighton, UK},
 author = {Nava, Emily and Tepperman, Joseph and Goldstein, Louis and Zubizarreta, Maria Luisa and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/nava_interspeech2009.pdf},
 month = {Sep},
 title = {Connecting rhythm and prominence in automatic ESL pronunciation scoring},
 year = {2009}
}

@INPROCEEDINGS{Plangprasopchok09www,
  AUTHOR =       {Anon Plangprasopchok and Kristina Lerman},
  TITLE =        {Constructing Folksonomies from User-specified Relations on Flickr},
  BOOKTITLE =    {Proceedings of 18th International World Wide Web Conference (WWW)},
  YEAR =         {2009},
  keywords =     {social-annotation},
    month={May},
  urlPaper={http://www.isi.edu/~lerman/papers/fp500-plangprasopchok.pdf},
}

@inproceedings{tsiartas09_interspeech,
 address = {Brighton, UK},
 author = {Tsiartas, Andreas and Ghosh, Prasanta Kumar and Georgiou, Panayiotis and Narayanan, Shrikanth S.},
 bib2html_rescat = {mica},
 booktitle = {Proceedings of InterSpeech},
 doi = {https://doi.org/10.1109/icassp.2011.5947635},
 link = {http://sail.usc.edu/publications/files/TsiartasInterSpeech2009.pdf},
 month = {Sep},
 title = {Context-driven automatic bilingual movie subtitle alignment},
 year = {2009}
}

@inproceedings{Kalinli2009Continuousspeechrecognitionusing,
 address = {Brighton, UK},
 author = {Kalinli, Ozlem and Narayanan, Shrikanth S.},
 bib2html_rescat = {speechlinks},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/KalinliInterSpeech2009.pdf},
 month = {Sep},
 title = {Continuous speech recognition using attention shift decoding with soft decision},
 year = {2009}
}

@inproceedings{benzel2009current,
  title={Current developments in DETER cybersecurity testbed technology},
  author={Benzel, Terry and Braden, Bob and Faber, Ted and Mirkovic, Jelena and Schwab, Steve and Sollins, Karen and Wroclawski, John},
  booktitle={Cybersecurity Applications \& Technology Conference For Homeland Security (CATCH).},
  pages={57--70},
  year={2009},
  organization={IEEE}
}

@Article{wes:dnssecinpractice,
author =        "Suresh Krishnaswamy and Wes Hardaker and Russ Mundy",
title =         "{DNSSEC} in Practice: Using {DNSSEC-Tools} to Deploy {DNSSEC}",
journal =       "Conference For Homeland Security, 2009. CATCH '09. Cybersecurity Applications \& Technology",
year =          2009,
month =         03,
day =           03,
url =           "http://ieeexplore.ieee.org/abstract/document/4804422/",
myorganization =        "PARSONS",
abstract = "The Domain Name System ({DNS}) is one of the core infrastructure components of the Internet. {DNS} data is also trivial to spoof. The security extensions to {DNS} ({DNSSEC}) provide a mechanism for users to verify the origin authenticity and integrity of {DNS} data based on cryptographic signatures. {DNSSEC} as a technology has steadily matured over the past several years and a number of tools and services that facilitate performing {DNSSEC}-related operations have emerged during this period. This paper gives an overview of using existing tools and utilities from the {DNSSEC-Tools} 1 suite to build environments that support {DNSSEC} along the complete path from the authoritative name server where domain data resides to the end-application that uses {DNS} data.",
}


%%
%% U. Lausanne
%%

The Domain Name System (DNS) is one of the core infrastructure components of the Internet. DNS data is also trivial to spoof. The security extensions to DNS (DNSSEC) provide a mechanism for users to verify the origin authenticity and integrity of DNS data based on cryptographic signatures. DNSSEC as a technology has steadily matured over the past several years and a number of tools and services that facilitate performing DNSSEC-related operations have emerged during this period. This paper gives an overview of using existing tools and utilities from the DNSSEC-Tools 1 suite to build environments that support DNSSEC along the complete path from the authoritative name server where domain data resides to the end-application that uses DNS data.

@inproceedings{yao_data_2009,
	address = {Orlando, Florida},
	title = {Data {Analysis} for {Massively} {Distributed} {Simulations}},
	booktitle = {Interservice/{Industry} {Training}, {Simulation}, and {Education} {Conference} ({I}/{ITSEC}) 2009},
	author = {Yao, Ke-Thia and Lucas, Robert F. and Ward, Craig E. and Wagenbreth, Gene and Gottschalck, Thomas D.},
	year = {2009},
}

@inproceedings{DBLP:conf/esaw/GrothMMOLG09,
  author       = {Paul Groth and
                  Simon Miles and
                  Sanjay Modgil and
                  Nir Oren and
                  Michael Luck and
                  Yolanda Gil},
  editor       = {Huib Aldewereld and
                  Virginia Dignum and
                  Gauthier Picard},
  title        = {Determining the Trustworthiness of New Electronic Contracts},
  booktitle    = {Engineering Societies in the Agents World X, 10th International Workshop,
                  {ESAW} 2009, Utrecht, The Netherlands, November 18-20, 2009. Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {5881},
  pages        = {132--147},
  publisher    = {Springer},
  year         = {2009},
  url          = {https://doi.org/10.1007/978-3-642-10203-5\_12},
  doi          = {10.1007/978-3-642-10203-5\_12},
  timestamp    = {Mon, 05 Feb 2024 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/esaw/GrothMMOLG09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{barnhart2009development,
  title={Development and Operation of a Micro-Satellite Dynamic Test Facility for Distributed Flight Operations},
  author={Barnhart, David and Barrett, Tim and Sachs, Jeff and Will, Peter},
  booktitle={AIAA Space 2009 Conference},
  month = sep,
  year={2009},
  isbn = {978-1-60086-980-8},
  doi = {10.2514/6.2009-6443}
}

@article{mcguyer2009diet,
  title={Diet soda and liquid nitrogen},
  author={McGuyer, Bart H and Brown, Justin M and Dang, Hoan B},
  journal={American Journal of Physics},
  volume={77},
  number={8},
  pages={677--677},
  year={2009},
  publisher={AIP Publishing}
}

@inproceedings{proc_donna:differentiatingheartbeatwveform:icdam09,
 address = {Washington, DC},
 author = {Spruijt-Metz, Donna and Li, Ming and Thatte, Gautam and Sukhatme, Gaurav and Annavaram, Murali and Mitra, Urbashi and Narayanan, Shrikanth S. and Medvidovic, Nenad},
 booktitle = {Proceedings of the International Conference on Diet and Activity Methods (ICDAM)},
 month = {Jun},
 title = {Differentiating physical activity modalities in youth using heartbeat waveform shape and differences between adjacent waveforms},
 year = {2009}
}

@InProceedings{ambite2009:ijcai,
  author = 	 {Jos\'{e} Luis Ambite and Bora Gazen and Craig A. Knoblock and Kristina Lerman and Thomas Russ},
  title = 	 {Discovering and Learning Semantic Models of Online Sources for Information Integration},
  booktitle = {Proceedings of the IJCAI Workshop on Information Integration on the Web},
  year = 	 {2009},
  address = 	 {Pasadena, CA},
  urlPaper={http://www.isi.edu/integration/papers/ambite09-iiweb.pdf},
  keywords =     {semantic-modeling},
    month={July},
}

@article{Silva2009Discriminativewaveletpacketfilter,
 author = {Silva, Jorge and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {10.1109/TSP.2009.2013898},
 journal = {IEEE Transactions on Signal Processing},
 link = {http://sail.usc.edu/publications/files/SilvaTSP2009.pdf},
 month = {May},
 number = {5},
 pages = {1796-1810},
 title = {Discriminative wavelet packet filter bank selection for pattern recognition},
 volume = {57},
 year = {2009}
}

@article{Liu2009Effectofbandwidthextension,
 author = {Liu, Chuping and Fu, Qian-Jie and Narayanan, Shrikanth S.},
 doi = {10.1121/1.3062145},
 journal = {Journal of the Acoustical Society of America},
 link = {http://sail.usc.edu/publications/files/liujasa2009.pdf},
 month = {Feb},
 number = {2},
 pages = {EL77-EL83},
 title = {Effect of bandwidth extension to telephone speech recognition in cochlear implant users},
 volume = {125},
 year = {2009}
}

@inproceedings{hussein_efficient_2009,
	location = {New York, {NY}, {USA}},
	title = {Efficient Band Approximation of Gram Matrices for Large Scale Kernel Methods on {GPUs}},
	rights = {All rights reserved},
	isbn = {978-1-60558-744-8},
	url = {http://doi.acm.org/10.1145/1654059.1654091},
	doi = {10.1145/1654059.1654091},
	series = {{SC} '09},
	abstract = {Kernel-based methods require O(N2) time and space complexities to compute and store non-sparse Gram matrices, which is prohibitively expensive for large scale problems. We introduce a novel method to approximate a Gram matrix with a band matrix. Our method relies on the locality preserving properties of space filling curves, and the special structure of Gram matrices. Our approach has several important merits. First, it computes only those elements of the Gram matrix that lie within the projected band. Second, it is simple to parallelize. Third, using the special band matrix structure makes it space efficient and {GPU}-friendly. We developed {GPU} implementations for the Affinity Propagation ({AP}) clustering algorithm using both our method and the {COO} sparse representation. Our band approximation is about 5 times more space efficient and faster to construct than {COO}. {AP} gains up to 6x speedup using our method without any degradation in its clustering performance.},
	pages = {31:1--31:10},
	booktitle = {Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis},
	publisher = {{ACM}},
	author = {Hussein, Mohamed and Abd-Almageed, Wael},
	urldate = {2019-05-01},
	year = {2009},
	note = {event-place: Portland, Oregon},
	keywords = {affinity propagation, {GPU}, Gram matrices, kernel methods, space filling curves, sparse matrices},
	file = {ACM Full Text PDF:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\UP986ZVL\\Hussein and Abd-Almageed - 2009 - Efficient Band Approximation of Gram Matrices for .pdf:application/pdf}
}

Kernel-based methods require O(N2) time and space complexities to compute and store non-sparse Gram matrices, which is prohibitively expensive for large scale problems. We introduce a novel method to approximate a Gram matrix with a band matrix. Our method relies on the locality preserving properties of space filling curves, and the special structure of Gram matrices. Our approach has several important merits. First, it computes only those elements of the Gram matrix that lie within the projected band. Second, it is simple to parallelize. Third, using the special band matrix structure makes it space efficient and GPU-friendly. We developed GPU implementations for the Affinity Propagation (AP) clustering algorithm using both our method and the COO sparse representation. Our band approximation is about 5 times more space efficient and faster to construct than COO. AP gains up to 6x speedup using our method without any degradation in its clustering performance.

@inproceedings{lee09_interpseech_2,
 address = {Brighton, UK},
 author = {Lee, Chi-Chun and Mower, Emily and Busso, Carlos and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {emotion},
 booktitle = {Proceedings of InterSpeech},
 doi = {https://doi.org/10.1016/j.specom.2011.06.004},
 link = {http://sail.usc.edu/publications/files/CCLee-SpeechComm-2011.pdf},
 month = {Sep},
 pages = {[2009 InterSpeech Emotion Challenge Award Winner]},
 title = {Emotion recognition using a hierarchical binary decision tree approach},
 year = {2009}
}

@inproceedings{thatte09_embs,
 address = {Minneapolis, MN},
 author = {Thatte, Gautam and Li, Ming and Emken, Adar and Mitra, Urbashi and Narayanan, Shrikanth S. and Annavaram, Murali and Spruijt-Metz, Donna},
 booktitle = {Proceedings of the Annual International IEEE Engineering in Medicine and Biology Society (EMBS) Conference},
 doi = {10.1109/IEMBS.2009.5334222},
 link = {http://sail.usc.edu/publications/files/Thatte_EMBC2009.pdf},
 month = {Sep},
 pages = {4678-4681},
 title = {Energy-efficient multihypothesis activity-detection for health-monitoring applications},
 volume = {1},
 year = {2009}
}

@article{2009PhRvD..79d4027S,
	Adsnote = {Provided by the SAO/NASA Astrophysics Data System},
	Adsurl = {http://adsabs.harvard.edu/abs/2009PhRvD..79d4027S},
	Archiveprefix = {arXiv},
	Author = {{Ver Steeg}, Greg and {Menicucci}, N.~C.},
	Doi = {10.1103/PhysRevD.79.044027},
	Eprint = {0711.3066},
	Journal = {Physical Review D},
	Keywords = {Quantum field theory in curved spacetime, Entanglement and quantum nonlocality},
	Month = feb,
	Number = 4,
	Primaryclass = {quant-ph},
	Title = {{Entangling power of an expanding universe}},
	Volume = 79,
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1103/PhysRevD.79.044027}}

@article{Chu2009Environmentalsoundrecognitionwith,
 author = {Chu, Selina and Narayanan, Shrikanth S. and Kuo, C.-C. Jay},
 bib2html_rescat = {},
 doi = {10.1109/TASL.2009.2017438},
 journal = {IEEE Transactions on Audio, Speech, and Language Processing},
 link = {http://sail.usc.edu/publications/files/SelinaChu-TASLP2009.pdf},
 month = {Aug},
 number = {6},
 pages = {1142-1158},
 title = {Environmental Sound Recognition with Time frequency Audio Features},
 volume = {17},
 year = {2009}
}

@inproceedings{ghosh09_interpseech,
 address = {Brighton, UK},
 author = {Ghosh, Prasanta Kumar and Narayanan, Shrikanth S. and Divenyi, Pierre and Goldstein, Louis and Saltzman, Elliot},
 bib2html_rescat = {span},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/ghoshinterspeech2009[ppt].pdf},
 month = {Sep},
 title = {Estimation of articulatory gesture patterns from speech acoustics},
 year = {2009}
}

@inproceedings{mower09_interspeech,
 address = {Brighton, UK},
 author = {Mower, Emily and Mataric, Maja J. and Narayanan, Shrikanth S.},
 bib2html_rescat = {emotion},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/MowerInterspeech2009.pdf},
 month = {Sep},
 title = {Evaluating evaluators: A case study in understanding the benefits and pitfalls of multi-evaluator modeling},
 year = {2009}
}

@inproceedings{BudalakotiDeAngelis,
address = {Vancouver, BC, Canada},
author = {Budalakoti, Suratna and DeAngelis, David and Barber, K Suzanne},
booktitle = {2009 International Conference on Computational Science and Engineering (IEEE CSE 2009)},
doi = {10.1109/CSE.2009.62},
file = {:home/dave/Documents/References/Budalakoti, DeAngelis, Barber - 2009 - Expertise Modeling and Recommendation in Online Question and Answer Forums.pdf:pdf},
isbn = {978-1-4244-5334-4},
pages = {481--488},
publisher = {IEEE},
title = {Expertise Modeling and Recommendation in Online Question and Answer Forums},
url = {https://ieeexplore.ieee.org/abstract/document/5284216 http://ieeexplore.ieee.org/document/5284216/},
year = {2009}
}

@inproceedings{michelson2009:ijcai,	
  author = "Matthew Michelson and Craig A. Knoblock",
  title = "Exploiting Background Knowledge to Build Reference Sets for Information Extraction",
  booktitle = "Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-2009)",
  address = "Pasadena, CA",
  year = "2009",
  urlPresentation= "http://usc-isi-i2.github.io/slides/michelson09-ijcai-slides.pdf",
  urlPaper= "http://usc-isi-i2.github.io/papers/michelson09-ijcai.pdf",
  Keywords = {"Information Extraction"}
}

@inproceedings{DBLP:conf/eScience/GilGRF09,
  author       = {Yolanda Gil and
                  Paul Groth and
                  Varun Ratnakar and
                  Christian Fritz},
  title        = {Expressive Reusable Workflow Templates},
  booktitle    = {Fifth International Conference on e-Science, e-Science 2009, 9-11
                  December 2009, Oxford, {UK}},
  pages        = {344--351},
  publisher    = {{IEEE} Computer Society},
  year         = {2009},
  url          = {https://doi.org/10.1109/e-Science.2009.55},
  doi          = {10.1109/E-SCIENCE.2009.55},
  timestamp    = {Fri, 24 Mar 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/eScience/GilGRF09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@incollection{chiang09:lncs,
	Author = {Yao-Yi Chiang and Craig A. Knoblock},
	booktitle = {Graphics Recognition: Achievements, Challenges, and Evolution, Selected Papers of the 8th International Workshop on Graphics Recognition (GREC), Lecture Notes in Computer Science, 6020},
	editors = {Jean-Marc Ogier and Wenyin Liu and Josep Llad�s},
	Publisher = "Springer",
	Address = "New York",
	Pages = {93-105},
	Title = {Extracting Road Vector Data from Raster Maps},
	Year = {2009},
	urlPaper = "http://usc-isi-i2.github.io/papers/chiang09-lncs.pdf",
       	Keywords = {"Map Extraction"}
	}

@article{goldberg09:ijgis,
	Author = "Daniel W. Goldberg and John P. Wilson and Craig A. Knoblock",
	Title = "Extracting geographic Features from the internet to automatically build detailed regional gazetteers",
	Journal = "International Journal of Geographic Information Science",
	Year = 2009,
	Volume = 23, 
	Number = 1,
	Pages = "92-128",
	urlLink= "http://www.informaworld.com/openurl?genre=article&issn=1365%2d8816&volume=23&issue=1&spage=93",
      	Keywords = {"Building Gazetteers"}}

@phdthesis{versteegthesis,
	Author = {Greg {Ver Steeg}},
	School = {California Institute of Technology},
	Title = {Foundational aspects of nonlocality},
	Url = {http://resolver.caltech.edu/CaltechETD:etd-05282009-115941},
	Year = {2009},
	Bdsk-Url-1 = {http://resolver.caltech.edu/CaltechETD:etd-05282009-115941}}

@article{DBLP:journals/sp/Gil09,
  author       = {Yolanda Gil},
  title        = {From data to knowledge to discoveries: Artificial intelligence and
                  scientific workflows},
  journal      = {Sci. Program.},
  volume       = {17},
  number       = {3},
  pages        = {231--246},
  year         = {2009},
  url          = {https://doi.org/10.3233/SPR-2009-0261},
  doi          = {10.3233/SPR-2009-0261},
  timestamp    = {Wed, 06 Oct 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/sp/Gil09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@Article{	  deelman2009gridcloud,
  Author	= {Ewa Deelman},
  URL		= {http://pegasus.isi.edu/publications/2009/Deelman-GridAndClouds.pdf},
  Title		= {Grids and Clouds: Making Workflow Applications Work in
		  Heterogeneous Distributed Environments},
  Journal	= {International Journal of High Performance Computing
		  Applications},
  Year		= {2009}
}

@INBOOK{Lerman09Handbook,
  AUTHOR =       {Kristina Lerman},
  editor =       {San Murugesan},
  TITLE =        {Handbook of Research on Web 2.0, 3.0, and X.0:
Technologies, Business, and Social Applications },
  CHAPTER =      {Leveraging User-specified Metadata to Personalize Image Search},
  pages =        {},
  PUBLISHER =    {IGI Global},
  YEAR =         {2009},
  keywords =     {social-annotation},
  urlPaper={http://www.isi.edu/integration/papers/personalization08.pdf},
}

@inproceedings{sgao2009a,
	author = {Shanyuan Gao and Andrew G. Schmidt and Ron Sass},
	booktitle = {Proceedings of the 19th Annual Conference on Field Programmable Logic and Applications (FPL{\textquoteright}09)},
	publisher = {IEEE Computer Society},
	title = {Hardware Implementation of MPI_Barrier on an FPGA Cluster},
	year = {2009}}

@article{kurc-et-al-hpc09,
  author    = {Tahsin M. Kur\c{c} and Shannon Hastings and Vijay S. Kumar and
               Stephen Langella and Ashish Sharma and Tony Pan and
               Scott Oster and David Ervin and Justin Permar and
               Sivaramakrishnan Narayanan and Yolanda Gil and Ewa Deelman and
               Mary W. Hall and Joel H. Saltz},
  title     = {High Performance Computing and Grid Computing for Integrative Biomedical Research},
  journal   = {Journal of High Performance Computing Applications},
  volume    = {23},
  number    = {3},
  year      = {2009},
  pages     = {252-264},
  ee        = {http://dx.doi.org/10.1177/1094342009106192},
  url = {https://knowledgecaptureanddiscovery.github.io/yolanda_gil_website/papers/kurc-et-al-hpc09.pdf }
}

@inproceedings{proc_jorge:histogramestdivergencerevisit:isit09,
 address = {Seoul, Korea},
 author = {Silva, Jorge and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
 doi = {10.1109/ISIT.2009.5205713},
 link = {http://sail.usc.edu/publications/files/silvaisit2009.pdf},
 month = {Jun},
 pages = {468-472},
 title = {Histogram-based estimation for the divergence revisited},
 year = {2009}
}

@inproceedings{mirkovic2009test,
  title={How to test DoS defenses},
  author={Mirkovic, Jelena and Fahmy, Sonia and Reiher, Peter and Thomas, Roshan K},
  booktitle={Proceedings of the 2009 Cybersecurity Applications \& Technology Conference for Homeland Security},
  pages={103--117},
  year={2009}
}

@article{Mower2009Humanperceptionofaudio-visual,
 author = {Mower, Emily and Mataric, Maja J. and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {10.1109/TMM.2009.2021722},
 journal = {IEEE Transactions on Multimedia},
 link = {http://sail.usc.edu/publications/files/MowerTM2009.pdf},
 month = {Aug},
 number = {5},
 pages = {843-855},
 title = {Human perception of audio-visual synthetic character emotion expression in the presence of ambiguous and conflicting information},
 volume = {11},
 year = {2009}
}

@inproceedings{han09_interspeech,
 address = {Brighton, UK},
 author = {Han, Kyu Jeong and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/HanInterSpeech2009[1].pdf},
 month = {Sep},
 pages = {1067-1070},
 title = {Improved Speaker Diarization of Meeting Speech With Recurrent Selection of Representative Speech Segments and Participant Interaction Pattern Modeling},
 year = {2009}
}

@InProceedings{Baker2009,
  author       = {Baker, Zachary K and Monson, Joshua S},
  title        = {In-situ FPGA debug driven by on-board microcontroller},
  booktitle    = {Field Programmable Custom Computing Machines, 2009. FCCM'09. 17th IEEE Symposium on},
  year         = {2009},
  pages        = {219--222},
  organization = {IEEE},
  doi          = {10.1109/FCCM.2009.9},
  month = apr
}

@inproceedings{mendon2009b,
	author = {Ashwin Mendon and Andrew G. Schmidt and Ron Sass},
	booktitle = {Proceedings of the 17th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM{\textquoteright}09)},
	publisher = {IEEE Computer Society},
	title = {Initial Implementation of a Hardware File System with Multiple Disk Support},
	year = {2009}}

@inproceedings{Singh2009,
	author= {K. Singh and R. Kost and K. Yoo and K. Parker and Crago, Stephen P.},
	title= {Integrated Development Environment and Parallel Performance Analysis Tools for Tile 64/ Maestro},
	booktitle= {Workshop on Multi-Core Processors for Space- Opportunities and Challenges held in conjunction with IEEE SMC-IT},
	location= {Pasadena, California},
	month= {July},
	year= {2009}
}

@InProceedings{ives2009:cidr,
  author = 	 {Zachary G. Ives and Craig A. Knoblock and Steven Minton and Marie Jacob and Partha Pratim Talukdar and Rattapoom Tuchinda and Jos\'{e} Luis Ambite and Maria Muslea and B. Cenk Gazen},
  title = 	 {Interactive Data Integration through Smart Copy \& Paste},
  booktitle = {Fourth Biennial Conference on Innovative Data Systems Research (CIDR) },
  year = 	 {2009},
  address = 	 {Pacific Grove, CA},
  month = 	 {January},
  urlPaper = "http://usc-isi-i2.github.io/papers/ives09-cidr.pdf",
  urlPresentation = "http://usc-isi-i2.github.io/slides/ives09-cidr-slides.pdf",
  Keywords = {"Interactive Data Integration"}
}

@inproceedings{Mower2009Interpretingambiguousemotionalexpressions,
 address = {Amsterdam, The Netherlands},
 author = {Mower, Emily and Metallinou, Angeliki and Lee, Chi-Chun and Kazemzadeh, Abe and Busso, Carlos and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {emotion},
 booktitle = {Proceedings of the International Conference on Affective Computing and Intelligent Interaction (ACII)},
 doi = {10.1109/ACII.2009.5349500},
 link = {http://sail.usc.edu/publications/files/moweracii2009.pdf},
 month = {Sep},
 title = {Interpreting ambiguous emotional expressions},
 year = {2009}
}

@inproceedings{Audhkhasi2009Lattice-basedlexicalcuesfor,
 address = {Merano, Italy},
 author = {Audhkhasi, Kartik and Georgiou, Panayiotis and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)},
 doi = {10.1109/ASRU.2009.5373419},
 link = {http://sail.usc.edu/publications/files/audhkhasi_asru2009.pdf},
 month = {Dec},
 title = {Lattice-based lexical cues for word fragment detection in conversational speech},
 year = {2009}
}

@INPROCEEDINGS{Ghosh09icwsm,
  AUTHOR =       {Rumi Ghosh and Kristina Lerman},
  TITLE =        {Leaders and Negotiators: An Influence-based Metric for Rank},
  BOOKTITLE =    {Proceedings of 3rd International Conference on Weblogs and Social Media (Poster)},
  YEAR =         {2009},
  keywords =     {social-networks},
}

@inproceedings{ gil-etal-ijcaiwikiAI-09,
 title = {Leveraging Social Networking Sites to Acquire Rich Task Structure},
 author = {Yolanda Gil and Paul Groth and Varun Ratnakar},
 booktitle = { Proceedings of the IJCAI Workshop on User-Contributed Knowledge and Artificial Intelligence: An Evolving Synergy (WikiAI), held in conjunction with the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI)},
 address = {Pasadena, CA},
  year = {2009},
 url = {https://knowledgecaptureanddiscovery.github.io/yolanda_gil_website/papers/gil-etal-ijcaiwikiAI-09.pdf }
 }

@article{vasilakis2009limits,
  title={Limits on new long range nuclear spin-dependent forces set with a K- He 3 comagnetometer},
  author={Vasilakis, G and Brown, JM and Kornack, TW and Romalis, MV},
  journal={Physical review letters},
  volume={103},
  number={26},
  pages={261801},
  year={2009},
  publisher={APS}
}

@TechReport{Park09a,
	author = 	"Unkyu Park and John Heidemann",
	title = 	"Low-latency Synchronization of Loosely-coupled Sensornet Republishing",
	institution = 	"USC/Information Sciences Institute",
	month = 	apr,
	year = 		2009,
	sortdate = "2009-04-01",
	project = "ilense, siss",
	jsubject = "sensornet_sharing",
	note = "updated June 2010 (original at \url{http://www.isi.edu/%7ejohnh/PAPERS/Park09a_200904.pdf})",
	number =	"ISI-TR-2009-660b",
	location = 	"johnh: pafile",
	keywords = 	"sensornet, sensor-internet, republishing,
                  synchronization, RSS",
	url =		"http://www.isi.edu/%7ejohnh/PAPERS/Park09a.html",
	pdfurl =	"http://www.isi.edu/%7ejohnh/PAPERS/Park09a.pdf",
	myorganization =	"USC/Information Sciences Institute",
	copyrightholder = "authors",
	abstract = "Today many individual deployments of sensornets
                  are successful, but they will have much greater
                  impact when, rather than standing alone, they share
                  data across deployments so each can build upon the
                  others.  We expect data to be shared over the
                  Internet, and as the number of processing and
                  reprocessing steps grows, \emph{timely data
                  synchronization} is increasingly important.  Today,
                  such sharing is often hard-coded or driven by
                  fixed-interval polling.  Fixed-interval polling can
                  provide poor worst-case performance (mean latency
                  approaching the data generation period), and best
                  performance requires careful manual configuration of
                  both poll period and phase.  We instead propose
                  \emph{Data Generation Tracking} (DGT), a new family
                  of adaptive polling algorithms that \emph{learn and
                  predict} good times to pull data to minimize both
                  latency and unfruitful queries.  Our approach avoids
                  manual configuration and automatically adapts to
                  outages and changes in data generation rate.  To
                  evaluate our work, we examine four sensornet
                  deployments and develop a rough \emph{model of
                  sensornet data generation}.  We then use this model
                  and replay of real traces to evaluate DGT, finding
                  that, depending on application, its median latency
                  is only 10--30\% of that of fixed-interval polling,
                  with a configurable rate of network load that is the
                  same or slightly higher.",
}

Today many individual deployments of sensornets are successful, but they will have much greater impact when, rather than standing alone, they share data across deployments so each can build upon the others. We expect data to be shared over the Internet, and as the number of processing and reprocessing steps grows, \emphtimely data synchronization is increasingly important. Today, such sharing is often hard-coded or driven by fixed-interval polling. Fixed-interval polling can provide poor worst-case performance (mean latency approaching the data generation period), and best performance requires careful manual configuration of both poll period and phase. We instead propose \emphData Generation Tracking (DGT), a new family of adaptive polling algorithms that \emphlearn and predict good times to pull data to minimize both latency and unfruitful queries. Our approach avoids manual configuration and automatically adapts to outages and changes in data generation rate. To evaluate our work, we examine four sensornet deployments and develop a rough \emphmodel of sensornet data generation. We then use this model and replay of real traces to evaluate DGT, finding that, depending on application, its median latency is only 10–30% of that of fixed-interval polling, with a configurable rate of network load that is the same or slightly higher.

@inproceedings{Crago2009,
	author= {Crago, Stephen P.},
	title= {Maestro Multi-Core Software},
	booktitle= {Workshop on Multi-Core Processors for Space- Opportunities and Challenges held in conjunction with Third IEEE International Conference on Space Mission Challenges for Information Technology},
	location= { Pasadena, California},
	month= {July},
	year= {2009}
}

@InProceedings{	  sakellariou2009coregrid,
  Author	= {Rizos Sakellariou and Henan Zhao and Ewa Deelman},
  URL		= {http://pegasus.isi.edu/publications/2009/coregrid09.pdf},
  Title		= {Mapping Workflows on Grid Resources: Experiments with the
		  Montage Workflow},
  BookTitle	= {CoreGrid},
  Year		= {2009}
}

@article{galstyan2009maximizing,
  title={Maximizing influence propagation in networks with community structure},
  author={Galstyan, Aram and Musoyan, Vahe and Cohen, Paul},
  journal={Physical Review E},
  volume={79},
  number={5},
  pages={056102},
  year={2009},
  publisher={APS}
}

@INPROCEEDINGS{michelson09:icai,
 author = 	{Matthew Michelson and Craig A. Knoblock},
 	title =  {Mining the Heterogeneous Transformations Between Data Sources to Aid Record Linkage},
 	booktitle = {Proceedings of the International Conference on Artificial Intelligence (ICAI)},
 	year = {2009},
	urlPresentation= "http://usc-isi-i2.github.io/slides/michelson09-icai-slides.pdf",
	urlPaper= "http://usc-isi-i2.github.io/papers/michelson09-icai.pdf",
      	Keywords = {"Record Linkage"}
}

@inproceedings{Crago2010,
	author= {Crago, Stephen P.},
	title= {Mission-Critical Space Software for Multi-Core Processors},
	booktitle= {Workshop on Flight Software},
	location= {Pasadena, California},
	month= {November},
	year= {2009}
}

@inproceedings{oikonomou2009modeling,
  title={Modeling human behavior for defense against flash-crowd attacks},
  author={Oikonomou, Georgios and Mirkovic, Jelena},
  booktitle={2009 IEEE International Conference on Communications (ICC)},
  pages={1--6},
  year={2009},
  organization={IEEE}
}

@inproceedings{lee09_interpseech,
 address = {Brighton, UK},
 author = {Lee, Chi-Chun and Busso, Carlos and Lee, Sungbok and Narayanan, Shrikanth S.},
 bib2html_rescat = {care, emotion, bsp},
 booktitle = {Proceedings of InterSpeech},
 link = {http://sail.usc.edu/publications/files/LeeInterSpeech2009[2].pdf},
 month = {Sep},
 title = {Modeling mutual influence of interlocutor emotion states in dyadic spoken interactions},
 year = {2009}
}

@inproceedings{maheswaran2009multi,
  title={Multi-agent systems for the real world},
  author={Maheswaran, Rajiv and Rogers, Craig Milo and Sanchez, Romeo and Szekely, Pedro and Gati, Gergely and Smyth, Kevin and VanBuskirk, Chris},
  booktitle={Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems-Volume 2},
  pages={1281--1282},
  year={2009},
  organization={International Foundation for Autonomous Agents and Multiagent Systems}
}

@inproceedings{hussein_object_2009,
	title = {Object detection via boosted deformable features},
	rights = {All rights reserved},
	doi = {10.1109/ICIP.2009.5414561},
	abstract = {It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subregions with fixed relative locations and extents with respect to the object's image window. We introduce using deformable features with boosted ensembles. A deformable features adapts its location depending on the visual evidence in order to match the corresponding physical feature. Therefore, deformable features can better handle deformable objects. We empirically show that boosted ensembles of deformable features perform significantly better than boosted ensembles of fixed features for human detection.},
	eventtitle = {2009 16th {IEEE} International Conference on Image Processing ({ICIP})},
	pages = {1445--1448},
	booktitle = {2009 16th {IEEE} International Conference on Image Processing ({ICIP})},
	author = {Hussein, M. and Porikli, F. and Davis, L.},
	date = {2009-11},
	year = {2009},
	keywords = {Biological system modeling, boosted ensembles, Boosting, Computer science, Computer vision, Context modeling, deformable features, Deformable Features, Deformable models, Educational institutions, feature extraction, Head, human detection, Human Detection, Humans, object detection, Object detection, statistics, visual evidence},
	file = {IEEE Xplore Abstract Record:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\I28BE5Y4\\5414561.html:text/html}
}

It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subregions with fixed relative locations and extents with respect to the object's image window. We introduce using deformable features with boosted ensembles. A deformable features adapts its location depending on the visual evidence in order to match the corresponding physical feature. Therefore, deformable features can better handle deformable objects. We empirically show that boosted ensembles of deformable features perform significantly better than boosted ensembles of fixed features for human detection.

@article{allahverdyan2009maximum,
  title={On maximum a posteriori estimation of hidden Markov processes},
  author={Allahverdyan, Armen and Galstyan, Aram},
  journal={arXiv preprint arXiv:0906.1980},
  year={2009}
}
%%2008

@inproceedings{DBLP:conf/dcoss/ThatteRLGMNAS09,
  author    = {Gautam Thatte and
               Viktor Rozgic and
               Ming Li and
               Sabyasachi Ghosh and
               Urbashi Mitra and
               Shrikanth S. Narayanan and
               Murali Annavaram and
               Donna Spruijt{-}Metz},
  editor    = {Bhaskar Krishnamachari and
               Subhash Suri and
               Wendi Rabiner Heinzelman and
               Urbashi Mitra},
  title     = {Optimal Allocation of Time-Resources for Multihypothesis Activity-Level
               Detection},
  booktitle = {Distributed Computing in Sensor Systems, 5th {IEEE} International
               Conference, {DCOSS} 2009, Marina del Rey, CA, USA, June 8-10, 2009.
               Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {5516},
  pages     = {273--286},
  publisher = {Springer},
  year      = {2009},
  url       = {https://doi.org/10.1007/978-3-642-02085-8\_20},
  doi       = {10.1007/978-3-642-02085-8\_20},
  timestamp = {Tue, 03 Dec 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/conf/dcoss/ThatteRLGMNAS09.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{DBLP:conf/bodynets/ThatteR0GMNAS09,
  author    = {Gautam Thatte and
               Viktor Rozgic and
               Ming Li and
               Sabyasachi Ghosh and
               Urbashi Mitra and
               Shrikanth S. Narayanan and
               Murali Annavaram and
               Donna Spruijt{-}Metz},
  editor    = {William J. Kaiser and
               Chenyang Lu},
  title     = {Optimal time-resource allocation for activity-detection via multimodal
               sensing},
  booktitle = {4th International {ICST} Conference on Body Area Networks, {BODYNETS}
               2009, Los Angeles, CA, USA, April 1-3, 2009},
  pages     = {14},
  publisher = {{ICST}},
  year      = {2009},
  url       = {https://doi.org/10.4108/ICST.BODYNETS2009.6030},
  doi       = {10.4108/ICST.BODYNETS2009.6030},
  timestamp = {Tue, 03 Dec 2019 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/conf/bodynets/ThatteR0GMNAS09.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@TechReport{Thatte09a,
	author = 	"Gautam Thatte and Urbashi Mitra and John Heidemann",
	title = 	"Parametric Methods for Anomaly Detection in Aggregate Traffic",
	institution = 	"USC/Information Sciences Institute",
	year = 		2009,
	sortdate = 		"2009-08-01", 
	project = "ant, nocredit, madcat",
	jsubject = "chronological",
	number =	"ISI-TR-2009-663b",
	month = 	aug,
	jlocation = 	"johnh: pafile",
	keywords = 	"internet anonaly detection, DoS attack
                  detection, parameteric methods",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/Thatte09a.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/Thatte09a.pdf",
	myorganization =	"USC/Information Sciences Institute",
	note = "First issued August 2009; updated August 2010",
	copyrightholder = "authors",
	usessoftware = "stream_merger",
	abstract = "This paper develops parametric methods to detect network anomalies
using only aggregate traffic statistics in contrast to other works
requiring flow separation, even when the anomaly is a small fraction
of the total traffic.  By adopting simple statistical models for
anomalous and background traffic in the time-domain, one can estimate
model parameters in real-time, thus obviating the need for a long
training phase or manual parameter tuning.  The proposed bivariate
Parametric Detection Mechanism (bPDM) uses a sequential probability
ratio test, allowing for control over the false positive rate while
examining the trade-off between detection time and the strength of an
anomaly.  Additionally, it uses both traffic-rate and packet-size
statistics, yielding a bivariate model that eliminates most false
positives.  The method is analyzed using the bitrate SNR metric, which
is shown to be an effective metric for anomaly detection.  The
performance of the bPDM is evaluated in three ways:  first,
synthetically generated traffic provides for a controlled comparison
of detection time as a function of the anomalous level of traffic.
Second, the approach is shown to be able to detect controlled
artificial attacks over the USC campus network in varying real traffic
mixes.  Third, the proposed algorithm achieves rapid detection of real
denial-of-service attacks as determined by the replay of previously
captured network traces.  The method developed in this paper is able
to detect all attacks in these scenarios in a few seconds or less.
",
}

This paper develops parametric methods to detect network anomalies using only aggregate traffic statistics in contrast to other works requiring flow separation, even when the anomaly is a small fraction of the total traffic. By adopting simple statistical models for anomalous and background traffic in the time-domain, one can estimate model parameters in real-time, thus obviating the need for a long training phase or manual parameter tuning. The proposed bivariate Parametric Detection Mechanism (bPDM) uses a sequential probability ratio test, allowing for control over the false positive rate while examining the trade-off between detection time and the strength of an anomaly. Additionally, it uses both traffic-rate and packet-size statistics, yielding a bivariate model that eliminates most false positives. The method is analyzed using the bitrate SNR metric, which is shown to be an effective metric for anomaly detection. The performance of the bPDM is evaluated in three ways: first, synthetically generated traffic provides for a controlled comparison of detection time as a function of the anomalous level of traffic. Second, the approach is shown to be able to detect controlled artificial attacks over the USC campus network in varying real traffic mixes. Third, the proposed algorithm achieves rapid detection of real denial-of-service attacks as determined by the replay of previously captured network traces. The method developed in this paper is able to detect all attacks in these scenarios in a few seconds or less.

@inproceedings{collins2009payoff,
  title={Payoff Based IDS Evaluation.},
  author={Collins, Michael and RedJack, LLC},
  booktitle={CSET},
  year={2009}
}

@InProceedings{	  groth2009pipeline,
  Author	= {Paul Groth and Ewa Deelman and Gideon Juve and Gaurang
		  Mehta and Bruce Berriman},
  URL		= {http://pegasus.isi.edu/publications/2009/GrothP-PipelineCentric.pdf},
  Title		= {Pipeline-Centric Provenance Model},
  BookTitle	= {4th Workshop on Workflows in Support of Large-Scale
		  Science (WORKS 09)},
  Year		= {2009}
}

@article{Ghosh2009Pitchcontourstylizationusing,
 author = {Ghosh, Prasanta Kumar and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 doi = {10.1109/LSP.2009.2025824},
 journal = {IEEE Signal Processing Letters},
 link = {http://sail.usc.edu/publications/files/ghoshspl2009.pdf},
 month = {Sep},
 number = {9},
 pages = {810-813},
 title = {Pitch contour stylization using an optimal piecewise polynomial approximation},
 volume = {16},
 year = {2009}
}

@inproceedings{black09_interpseech,
 address = {Brighton, UK},
 author = {Black, Matthew P. and Tepperman, Joseph and Lee, Sungbok and Narayanan, Shrikanth S.},
 booktitle = {Proceedings of InterSpeech},
 keyword = {childrens speech, disfluency detection, feature selection, pronunciation verification, reading assessment},
 link = {http://sail.usc.edu/publications/files/blackinterspeech2009.pdf},
 month = {Sep},
 title = {Predicting childrens reading ability using evaluator-informed features},
 year = {2009}
}

@proceedings{k-cap-09,
  editor    = {Yolanda Gil and
               Natasha Fridman Noy},
  title     = {Proceedings of the 5th International Conference on Knowledge
               Capture (K-CAP)},
  address = {Redondo Beach, CA},
  publisher = {Association for Computing Machinery},
  year      = {2009}
}

@article{Kalinli2009Prominencedetectionusingauditory,
 author = {Kalinli, Ozlem and Narayanan, Shrikanth S.},
 doi = {10.1109/TASL.2009.2014795},
 journal = {IEEE Transactions on Audio, Speech, and Language Processing},
 keyword = {accent, auditory attention, auditory gist, lexical rules, prominence, stress, syntax, task-dependent},
 link = {http://sail.usc.edu/publications/files/kalinlitaslp2009.pdf},
 month = {Jul},
 number = {5},
 pages = {1009-1024},
 title = {Prominence detection using auditory attention cues and task-dependent high level information},
 volume = {17},
 year = {2009}
}

@inproceedings{jin2009querymarvel,
  title={QueryMarvel: a visual query language for temporal patterns using comic strips},
  author={Jin, Jing and Szekely, Pedro},
  booktitle={Visual Languages and Human-Centric Computing, 2009. VL/HCC 2009. IEEE Symposium on},
  pages={207--214},
  year={2009},
  organization={IEEE}
}

@inproceedings{kline2009rad,
  title={RAD: Reflector attack defense using message authentication codes},
  author={Kline, Erik and Beaumont-Gay, Matt and Mirkovic, Jelena and Reiher, Peter},
  booktitle={2009 Annual Computer Security Applications Conference (ACSAC)},
  pages={269--278},
  year={2009},
  organization={IEEE}
}

@inproceedings{Ramanarayanan2009Real-timeMRItrackingof,
 address = {Portland, Oregon},
 author = {Ramanarayanan, Vikram and Bresch, Erik and Byrd, Dani and Goldstein, Louis and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 booktitle = {Proceedings of the Meeting of the Acoustical Society of America},
 doi = {10.1121/1.4783766},
 month = {May},
 title = {Real-time MRI tracking of articulation during grammatical and ungrammatical pauses in speech},
 year = {2009}
}

@inproceedings{yildirim09_wocci,
 address = {Cambridge, MA},
 author = {Yildirim, Serdar and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the Workshop on Child, Computer and Interaction},
 doi = {10.1145/1640377.1640391},
 link = {http://sail.usc.edu/publications/files/yildirimwocci2009.pdf},
 month = {Nov},
 title = {Recognizing childs emotional state in problem-solving child-machine interactions},
 year = {2009}
}

@article{Bresch2009Regionsegmentationinthe,
 author = {Bresch, Erik and Narayanan, Shrikanth S.},
 bib2html_rescat = {span},
 doi = {https://doi.org/10.1109/tmi.2008.928920},
 journal = {IEEE Transactions on Medical Imaging},
 link = {http://sail.usc.edu/publications/files/04580124.pdf},
 month = {Mar},
 number = {3},
 pages = {323-338},
 title = {Region segmentation in the frequency domain applied to upper airway real-time magnetic resonance images},
 volume = {28},
 year = {2009}
}

@article{2008arXiv0811.3771V,
	Adsnote = {Provided by the SAO/NASA Astrophysics Data System},
	Adsurl = {http://adsabs.harvard.edu/abs/2008arXiv0811.3771V},
	Author = {{Ver Steeg}, Greg and {Wehner}, S.},
	Journal = {Quantum Information and Computation},
	Keywords = {Quantum Physics},
	Pages = {0801-0832},
	Title = {{Relaxed uncertainty relations and information processing}},
	Volume = 9,
	Year = {2009}}

@Article{He09a,
	author = "Xinming He and Christos Papadopoulos and John
 Heidemann and Urbashi Mitra and Usman Riaz",
	title = "Remote Detection of Bottleneck Links Using Spectral and Statistical Methods",
	journal = 	"Computer Networks",
	year = 		2009,
	sortdate = 		"2009-02-01",
	project = "ant, madcat, nocredit",
	jsubject = "spectral_network",
	publisher = "Elsevier Science Publishing Co., Inc.",
	volume = 	53,
	number = 	3,
	pages = 	"279--298",
	month = 	feb,
	jlocation = 	"johnh: pafile",
	doi = 	"	10.1016/j.comnet.2008.10.001",
	jlocation =	"johnh: pafile",
	keywords =	"spectral analysis, bottleneck detection",
	copyrightholder = "Elsevier Science Publishing Co., Inc.",
	copyrightterms = 	"Single photocopies of single articles 	may be made for personal use as allowed by national copyright 	laws. Permission of the Publisher and payment of a fee is required for 	all other photocopying, including multiple or systematic copying, 	copying for advertising or promotional purposes, resale, and all forms 	of document delivery. Special rates are available for educational 	institutions that wish to make photocopies for non-profit educational 	classroom use. Permissions may be sought directly from:  Elsevier 	Global Rights Department / P.O. Box 800 / Oxford OX5 1DX, UK / 	phone: (+44) 1865 843830 / 	fax: (+44) 1865 853333 / 	e-mail: [email protected] ",
	url =		"https://ant.isi.edu/%7ejohnh/PAPERS/He09a.html",
	pdfurl =	"https://ant.isi.edu/%7ejohnh/PAPERS/He09a.pdf",
	myorganization =	"USC/Information Sciences Institute",

	abstract = "
Persistently saturated links are abnormal conditions that indicate
bottlenecks in Internet traffic. Network operators are interested in
detecting such links for troubleshooting, to improve capacity planning
and traffic estimation, and to detect denial-of-service attacks.
Currently bottleneck links can be detected either locally, through
SNMP information, or remotely, through active probing or passive
flow-based analysis.  However, local SNMP information may not be
available due to administrative restrictions, and existing remote
approaches are not used systematically because of their network or
computation overhead.  This paper proposes a new approach to remotely
detect the presence of bottleneck links using spectral and statistical
analysis of traffic.  Our approach is \emph{passive}, operates on
\emph{aggregate traffic} without flow separation, and supports
\emph{remote detection} of bottlenecks, addressing some of the major
limitations of existing approaches.  Our technique assumes that
traffic through the bottleneck is dominated by packets with a common
size (typically the maximum transfer unit, for reasons discussed in
Section 5.1.  With this assumption, we observe
that bottlenecks imprint periodicities on packet transmissions based
on the packet size and link bandwidth.  Such periodicities manifest
themselves as strong frequencies in the spectral representation of the
aggregate traffic observed at a downstream monitoring point.  We
propose a detection algorithm based on rigorous statistical methods to
detect the presence of bottleneck links by examining strong
frequencies in aggregate traffic.  We use data from live Internet
traces to evaluate the performance of our algorithm under various
network conditions. Results show that with proper parameters our
algorithm can provide excellent accuracy (up to 95\%) even if the
traffic through the bottleneck link accounts for less than 10\% of the
aggregate traffic.
",
}

Persistently saturated links are abnormal conditions that indicate bottlenecks in Internet traffic. Network operators are interested in detecting such links for troubleshooting, to improve capacity planning and traffic estimation, and to detect denial-of-service attacks. Currently bottleneck links can be detected either locally, through SNMP information, or remotely, through active probing or passive flow-based analysis. However, local SNMP information may not be available due to administrative restrictions, and existing remote approaches are not used systematically because of their network or computation overhead. This paper proposes a new approach to remotely detect the presence of bottleneck links using spectral and statistical analysis of traffic. Our approach is \emphpassive, operates on \emphaggregate traffic without flow separation, and supports \emphremote detection of bottlenecks, addressing some of the major limitations of existing approaches. Our technique assumes that traffic through the bottleneck is dominated by packets with a common size (typically the maximum transfer unit, for reasons discussed in Section 5.1. With this assumption, we observe that bottlenecks imprint periodicities on packet transmissions based on the packet size and link bandwidth. Such periodicities manifest themselves as strong frequencies in the spectral representation of the aggregate traffic observed at a downstream monitoring point. We propose a detection algorithm based on rigorous statistical methods to detect the presence of bottleneck links by examining strong frequencies in aggregate traffic. We use data from live Internet traces to evaluate the performance of our algorithm under various network conditions. Results show that with proper parameters our algorithm can provide excellent accuracy (up to 95%) even if the traffic through the bottleneck link accounts for less than 10% of the aggregate traffic.

@inproceedings{proc_andreas:wordboundarydetection:icassp09,
 address = {Taipei, Taiwan},
 author = {Tsiartas, Andreas and Ghosh, Prasanta Kumar and Georgiou, Panayiotis and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
 doi = {10.1109/ICASSP.2009.4960701},
 link = {http://sail.usc.edu/publications/files/tsiartasicassp2009.pdf},
 month = {Apr},
 pages = {4785-4788},
 title = {Robust word boundary detection in spontaneous speech using acoustic and lexical cues},
 year = {2009}
}

@inproceedings{barnhart2009spidr,
  title={SPIDR: Integrated Systems Engineering Design-to-Simulation Software for Satellite Build},
  author={Barnhart, David A and Kichkaylo, Tatiana and Hoag, Lucy},
  booktitle={Conference on Systems Engineering Research},
  year={2009},
  month = jan
}

@Article{Yoon09a,
	author = 	"SunHee Yoon and Wei Ye and John Heidemann and
                  Brian Littlefield and Cyrus Shahabi",
	title = 	"SWATS: Wireless Sensor Networks for
                  Steamflood and Waterflood Pipeline Monitoring",
	journal = 	"IEEE Network Magazine",
	year = 		2009,
	sortdate = "2009-07-09",
	project = "ilense, imsc, pecase, cens, cisoft",
	jsubject = "chronological",
	note = 	"accepted in 2009; appears as [Yoon11a]",
	location = 	"johnh: pafile",
	keywords = 	"sensornet, oilfield, steamflood, waterflood",
	  url =		"http://www.isi.edu/%7ejohnh/PAPERS/Yoon09a.html",
	  pdfurl =	"http://www.isi.edu/%7ejohnh/PAPERS/Yoon09a.pdf",
	  copyrightholder = "IEEE",
	  copyrightterms = "	Personal use of this material is permitted.  However, 	permission to reprint/republish this material for advertising 	or promotional purposes or for creating new collective works         for resale or redistribution to servers or lists, 	or to reuse any copyrighted component of this work in other works 	must be obtained from the IEEE. ",
	  myorganization = 	"USC/Information Sciences Institute",
	abstract = "
State-of-the-art anomaly detection systems deployed in the oilfields
are expensive, not scalable to a large number of sensors, require
manual operation, and provide data with a long delay. To overcome
these problems, we design a wireless sensor network system that
detects, identifies, and localizes major anomalies such as blockage
and leakage that arise in steamflood and waterflood pipelines in
oilfields. A sensor network consists of small, inexpensive nodes
equipped with embedded processors and wireless communication, which
enables flexible deployment and close observation of phenomena without
human intervention. Our sensor network based system, SWATS (Steamflood
and WAterflood Tracking System), aims to allow continuous monitoring
of the steamflood and waterflood systems with low cost, short delay,
and fine granularity coverage while providing high accuracy and
reliability. The anomaly detection and identification is challenging
because of the inherent inaccuracy and unreliability of sensors and
the transient characteristics of the flows. Moreover, observation by a
single node cannot capture the topological effects on the transient
characteristics of steam and water fluid to disambiguate similar
problems and false alarms. We address these hurdles by utilizing
multi-modal sensing and multi-sensor collaboration and exploiting
temporal and spatial patterns of the sensed phenomena.
",
}

%	title = 	"{SWATS}: Wireless Sensor Networks for
%                  Steamflood and Waterflood Pipeline Monitoring",

State-of-the-art anomaly detection systems deployed in the oilfields are expensive, not scalable to a large number of sensors, require manual operation, and provide data with a long delay. To overcome these problems, we design a wireless sensor network system that detects, identifies, and localizes major anomalies such as blockage and leakage that arise in steamflood and waterflood pipelines in oilfields. A sensor network consists of small, inexpensive nodes equipped with embedded processors and wireless communication, which enables flexible deployment and close observation of phenomena without human intervention. Our sensor network based system, SWATS (Steamflood and WAterflood Tracking System), aims to allow continuous monitoring of the steamflood and waterflood systems with low cost, short delay, and fine granularity coverage while providing high accuracy and reliability. The anomaly detection and identification is challenging because of the inherent inaccuracy and unreliability of sensors and the transient characteristics of the flows. Moreover, observation by a single node cannot capture the topological effects on the transient characteristics of steam and water fluid to disambiguate similar problems and false alarms. We address these hurdles by utilizing multi-modal sensing and multi-sensor collaboration and exploiting temporal and spatial patterns of the sensed phenomena.

@inproceedings{kalinli09_mmsp,
 address = {Rio de Janeiro, Brazil},
 author = {Kalinli, Ozlem and Sundaram, Shiva and Narayanan, Shrikanth S.},
 bib2html_rescat = {},
 booktitle = {Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP)},
 doi = {https://doi.org/10.1109/mmsp.2009.5293267},
 link = {http://sail.usc.edu/publications/files/KalinliMMSP2009.pdf},
 month = {Oct},
 title = {Saliency-driven unstructured acoustic scene classification using latent perceptual indexing},
 year = {2009}
}

@inproceedings{DBLP:conf/aaaiss/GrothG09,
  author       = {Paul Groth and
                  Yolanda Gil},
  title        = {Scaffolding Instructions to Learn Procedures from Users},
  booktitle    = {Agents that Learn from Human Teachers, Papers from the 2009 {AAAI}
                  Spring Symposium, Technical Report SS-09-01, Stanford, California,
                  USA, March 23-25, 2009},
  pages        = {63--70},
  publisher    = {{AAAI}},
  year         = {2009},
  url          = {http://www.aaai.org/Library/Symposia/Spring/2009/ss09-01-010.php},
  timestamp    = {Tue, 04 Aug 2020 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/aaaiss/GrothG09.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@InProceedings{	  juve2009ec2,
  Author	= {Gideon Juve and Ewa Deelman and Karan Vahi and Gaurang
		  Mehta and Bruce Berriman and Benjamin P. Berman and Philip
		  J. Maechling},
  URL		= {http://pegasus.isi.edu/publications/2009/JuveG-EC2.pdf},
  Title		= {Scientific Workflow Applications on Amazon EC2},
  BookTitle	= {Workshop on Cloud-based Services and Applications},
  Year		= {2009}
}

@misc{rfc5592,
  author="D. Harrington and J. Salowey and W. Hardaker",
  title="{Secure Shell Transport Model for the Simple Network Management Protocol (SNMP)}",
  howpublished="RFC 5592 (Proposed Standard)",
  series="Internet Request for Comments",
  type="RFC",
  number="5592",
  year=2009,
  month=06,
  issn="2070-1721",
  publisher="RFC Editor",
  institution="RFC Editor",
  organization="RFC Editor",
  address="Fremont, CA, USA",
  url="https://www.rfc-editor.org/rfc/rfc5592.txt",
  key="RFC 5592",
  abstract={This memo describes a Transport Model for the Simple Network Management Protocol (SNMP), using the Secure Shell (SSH) protocol. This memo also defines a portion of the Management Information Base (MIB) for use with network management protocols in TCP/IP-based internets. In particular, it defines objects for monitoring and managing the Secure Shell Transport Model for SNMP. [STANDARDS-TRACK]},
  keywords="Network Management, Simple Network Management Protocol, SNMP, Secure Shell, SSH",
  doi="10.17487/RFC5592",
  }                  
                  

This memo describes a Transport Model for the Simple Network Management Protocol (SNMP), using the Secure Shell (SSH) protocol. This memo also defines a portion of the Management Information Base (MIB) for use with network management protocols in TCP/IP-based internets. In particular, it defines objects for monitoring and managing the Secure Shell Transport Model for SNMP. [STANDARDS-TRACK]