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Title: Signature system for video identification.
Creator: Medellin, Sebastian Possos., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Video signature techniques based on tomography images address the problem of video identification. This method relies on temporal segmentation and sampling strategies to build and determine the unique elements that will form the signature. In this thesis an extension for these methods is presented; first a new feature extraction method, derived from the previously proposed sampling pattern, is implemented and tested, resulting in a highly distinctive set of signature elements, second a robust...
Show moreVideo signature techniques based on tomography images address the problem of video identification. This method relies on temporal segmentation and sampling strategies to build and determine the unique elements that will form the signature. In this thesis an extension for these methods is presented; first a new feature extraction method, derived from the previously proposed sampling pattern, is implemented and tested, resulting in a highly distinctive set of signature elements, second a robust temporal video segmentation system is used to replace the original method applied to determine shot changes more accurately. Under a very exhaustive set of tests the system was able to achieve 99.58% of recall, 100% of precision and 99.35% of prediction precision.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/2683534
Subject Headings: Biometric identification, Image processing, Digital techniques, Pattern recognition systems, Data encryption (Computer science)
Format: Document (PDF)

Title: Sparse Coding and Compressed Sensing: Locally Competitive Algorithms and Random Projections.
Creator: Hahn, William E., Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Center for Complex Systems and Brain Sciences
Abstract/Description: For an 8-bit grayscale image patch of size n x n, the number of distinguishable signals is 256(n2). Natural images (e.g.,photographs of a natural scene) comprise a very small subset of these possible signals. Traditional image and video processing relies on band-limited or low-pass signal models. In contrast, we will explore the observation that most signals of interest are sparse, i.e. in a particular basis most of the expansion coefficients will be zero. Recent developments in sparse...
Show moreFor an 8-bit grayscale image patch of size n x n, the number of distinguishable signals is 256(n2). Natural images (e.g.,photographs of a natural scene) comprise a very small subset of these possible signals. Traditional image and video processing relies on band-limited or low-pass signal models. In contrast, we will explore the observation that most signals of interest are sparse, i.e. in a particular basis most of the expansion coefficients will be zero. Recent developments in sparse modeling and L1 optimization have allowed for extraordinary applications such as the single pixel camera, as well as computer vision systems that can exceed human performance. Here we present a novel neural network architecture combining a sparse filter model and locally competitive algorithms (LCAs), and demonstrate the networks ability to classify human actions from video. Sparse filtering is an unsupervised feature learning algorithm designed to optimize the sparsity of the feature distribution directly without having the need to model the data distribution. LCAs are defined by a system of di↵erential equations where the initial conditions define an optimization problem and the dynamics converge to a sparse decomposition of the input vector. We applied this architecture to train a classifier on categories of motion in human action videos. Inputs to the network were small 3D patches taken from frame di↵erences in the videos. Dictionaries were derived for each action class and then activation levels for each dictionary were assessed during reconstruction of a novel test patch. We discuss how this sparse modeling approach provides a natural framework for multi-sensory and multimodal data processing including RGB video, RGBD video, hyper-spectral video, and stereo audio/video streams.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004713, http://purl.flvc.org/fau/fd/FA00004713
Subject Headings: Artificial intelligence, Expert systems (Computer science), Image processing -- Digital techniques -- Mathematics, Sparse matrices
Format: Document (PDF)

Title: Sparse and low rank constraints on optical flow and trajectories.
Creator: Gibson, Joel, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this dissertation we apply sparse constraints to improve optical flow and trajectories. We apply sparsity in two ways. First, with 2-frame optical flow, we enforce a sparse representation of flow patches using a learned overcomplete dictionary. Second, we apply a low rank constraint to trajectories via robust coupling. We begin with a review of optical flow fundamentals. We discuss the commonly used flow estimation strategies and the advantages and shortcomings of each. We introduce the...
Show moreIn this dissertation we apply sparse constraints to improve optical flow and trajectories. We apply sparsity in two ways. First, with 2-frame optical flow, we enforce a sparse representation of flow patches using a learned overcomplete dictionary. Second, we apply a low rank constraint to trajectories via robust coupling. We begin with a review of optical flow fundamentals. We discuss the commonly used flow estimation strategies and the advantages and shortcomings of each. We introduce the concepts associated with sparsity including dictionaries and low rank matrices.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004286, http://purl.flvc.org/fau/fd/FA00004286
Subject Headings: Approximation theory -- Mathematical models, Computer vision, Image processing -- Digital techniques, Information visualization
Format: Document (PDF)

Title: DIGITAL IMAGE PROCESSING APPLIED TO CHARACTER RECOGNITION.
Creator: BEGUN, RALPH MURRAY., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: Surveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images....
Show moreSurveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images. A system architecture is proposed for a hardware based video speed image processor operating on local image windows. The possible implementation of this processor is outlined.
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Date Issued: 1982
PURL: http://purl.flvc.org/fcla/dt/14120
Subject Headings: Image processing--Digital techniques, Optical character recognition devices, Pattern recognition systems
Format: Document (PDF)

Title: Content-based image retrieval using relevance feedback.
Creator: Marques, Oge, Florida Atlantic University, Furht, Borko, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This dissertation presents the results of research that led to the development of a complete, fully functional, image search and retrieval system with relevance feedback capabilities, called MUSE (MUltimedia SEarch and Retrieval Using Relevance Feedback). Two different models for searching for a target image using relevance feedback have been proposed, implemented, and tested. The first model uses a color-based feature vector and employs a Bayesian learning algorithm that updates the...
Show moreThis dissertation presents the results of research that led to the development of a complete, fully functional, image search and retrieval system with relevance feedback capabilities, called MUSE (MUltimedia SEarch and Retrieval Using Relevance Feedback). Two different models for searching for a target image using relevance feedback have been proposed, implemented, and tested. The first model uses a color-based feature vector and employs a Bayesian learning algorithm that updates the probability of each image in the database being the target based on the user's actions. The second model uses cluster analysis techniques, a combination of color-, texture-, and edge(shape)-based features, and a novel approach to learning the user's goals and the relevance of each feature for a particular search. Both models follow a purely content-based image retrieval paradigm. The search process is based exclusively on image contents automatically extracted during the (off-line) feature extraction stage. Moreover, they minimize the number and complexity of required user's actions, in contrast with the complexity of the underlying search and retrieval engine. Results of experiments show that both models exhibit good performance for moderate-size, unconstrained databases and that a combination of the two outperforms any of them individually, which is encouraging. In the process of developing this dissertation, we also implemented and tested several image features and similarity measurement combinations. The result of these tests---performed under the query-by-example (QBE) paradigm---served as a reference in the choice of which features to use in the relevance feedback mode and confirmed the difficulty in encoding the understanding of image similarity into a combination of features and distances without human assistance. Most of the code written during the development of this dissertation has been encapsulated into a multifunctional prototype that combines image searching (with or without an example), browsing, and viewing capabilities and serves as a framework for future research in the subject.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/11954
Subject Headings: Information storage and retrieval systems, Image processing--Digital techniques, Feedback control systems
Format: Document (PDF)

Title: Methods and Algorithms for Human Detection in Video Sequences.
Creator: Pertuz, Carlos, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Lower prices of video sensors, security concerns and the need for better and faster algorithms to extract high level information from video sequences are all factors which have stimulated research in the area of automated video surveillance systems. In the context of security the analysis of human interrelations and their environment provides hints to proactively identify anomalous behavior. However, human detection is a necessary component in systems where the automatic extraction of higher...
Show moreLower prices of video sensors, security concerns and the need for better and faster algorithms to extract high level information from video sequences are all factors which have stimulated research in the area of automated video surveillance systems. In the context of security the analysis of human interrelations and their environment provides hints to proactively identify anomalous behavior. However, human detection is a necessary component in systems where the automatic extraction of higher level information, such as recognizing individuals' activities, is required. The human detection problem is one of classification. In general, motion, appearance and shape are the classification approaches a system can employ to perform human detection. Techniques representative of these approaches, such us periodic motion detection, skin color detection and MPEG-7 shape descriptors are implemented in this work. An infrastructure that allows data collection for such techniques was also implemented.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012538
Subject Headings: MPEG (Video coding standard), Image processing--Digital techniques, Form perception, Computer algorithms, Video compression
Format: Document (PDF)

Title: Image detection for a customizable user interface.
Creator: Polimeni, Joseph C., Florida Atlantic University, Mahgoub, Imad, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A user interface that has objects familiar to the user will be easier to use. In this thesis, a user interface that is customizable to any color bitmap is proposed. The most significant problem with this approach is the problem of finding objects in a color bitmap. A solution to the problem is proposed and evaluated using an analysis tool, developed for this thesis, called Workbench. Current image detection methods are evaluated and compared to the solution proposed using Workbench. The...
Show moreA user interface that has objects familiar to the user will be easier to use. In this thesis, a user interface that is customizable to any color bitmap is proposed. The most significant problem with this approach is the problem of finding objects in a color bitmap. A solution to the problem is proposed and evaluated using an analysis tool, developed for this thesis, called Workbench. Current image detection methods are evaluated and compared to the solution proposed using Workbench. The proposed solution is then evaluated for the YIQ and HSI color mappings. The results of this investigation and recommendations for future work is proposed.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15207
Subject Headings: User interfaces (Computer systems), Human-computer interaction, Image processing--Digital techniques
Format: Document (PDF)

Title: Image rectification/registration from a project management perspective: A review of various software.
Creator: Gammack-Clark, James Peter, Florida Atlantic University, Roberts, Charles
Abstract/Description: The project manager has much to deliberate when choosing a software package for image rectification/registration. He/she must be able to perform a cost analysis evaluation of the packages in question, and determine which package will provide the highest level of positional accuracy. Objective and subjective analysis of six software packages, ArcView Image Analysis, GeoMedia Pro, Arc/Info 8.1, ERMAPPER, ENVI and Idrisi 3.2, and their multiple products (polynomials and triangulations) provide...
Show moreThe project manager has much to deliberate when choosing a software package for image rectification/registration. He/she must be able to perform a cost analysis evaluation of the packages in question, and determine which package will provide the highest level of positional accuracy. Objective and subjective analysis of six software packages, ArcView Image Analysis, GeoMedia Pro, Arc/Info 8.1, ERMAPPER, ENVI and Idrisi 3.2, and their multiple products (polynomials and triangulations) provide the basis with which the project manager may attain this goal. He/she is familiarized with the user interface of each package, through detailed step-by-step methodology. Positional accuracy of each product is compared to Ground Control Points (GCPs) derived from a Differential Global Positioning System (DGPS). The accuracy of each product is also compared to the industry standard USGS DOQQ, and it is discovered that while simple rectification procedures may produce mean errors acceptable to the specifications of NMAS, the strictest application of these standards reveal that these products are not accurate enough to satisfy the USGS standards.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12829
Subject Headings: Computer software--Evaluation, Image processing--Digital techniques, Remote sensing
Format: Document (PDF)

Title: A visual perception threshold matching algorithm for real-time video compression.
Creator: Noll, John M., Florida Atlantic University, Pandya, Abhijit S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A barrier to the use of digital imaging is the vast storage requirements involved. One solution is compression. Since imagery is ultimately subject to human visual perception, it is worthwhile to design and implement an algorithm which performs compression as a function of perception. The underlying premise of the thesis is that if the algorithm closely matches visual perception thresholds, then its coded images contain only the components necessary to recreate the perception of the visual...
Show moreA barrier to the use of digital imaging is the vast storage requirements involved. One solution is compression. Since imagery is ultimately subject to human visual perception, it is worthwhile to design and implement an algorithm which performs compression as a function of perception. The underlying premise of the thesis is that if the algorithm closely matches visual perception thresholds, then its coded images contain only the components necessary to recreate the perception of the visual stimulus. Psychophysical test results are used to map the thresholds of visual perception, and develop an algorithm that codes only the image content exceeding those thresholds. The image coding algorithm is simulated in software to demonstrate compression of a single frame image. The simulation results are provided. The algorithm is also adapted to real-time video compression for implementation in hardware.
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Date Issued: 1992
PURL: http://purl.flvc.org/fcla/dt/14857
Subject Headings: Image processing--Digital techniques, Computer algorithms, Visual perception, Data compression (Computer science)
Format: Document (PDF)

Title: Optical Characterization ofPort Everglades Focusing on Underwater Visibility.
Creator: Whipple, Dustin E., Frisk, George V., Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: The development of an unmanned underwater vehicle at Florida Atlantic University with onboard optical sensors has prompted the temporal and spatial optical characterization of Port Everglades, with in-situ measurements of the turbidity, conductivity, and temperature. Water samples were collected for laboratory analysis where attenuation and absorption were measured with a bench top spectrometer. All of the measurements showed a high degree of variability within the port on a temporal and...
Show moreThe development of an unmanned underwater vehicle at Florida Atlantic University with onboard optical sensors has prompted the temporal and spatial optical characterization of Port Everglades, with in-situ measurements of the turbidity, conductivity, and temperature. Water samples were collected for laboratory analysis where attenuation and absorption were measured with a bench top spectrometer. All of the measurements showed a high degree of variability within the port on a temporal and spatial basis. Correlations were researched between the measured properties as well as tide and current. Temporal variations showed a high correlation to tidal height but no relation was found between turbidity and current, or salinity. Spatial variations were primarily determined by proximity to the port inlet. Proportionality constants were discovered to relate turbidity to scattering and absorption coefficients. These constants along with future turbidity measurements will allow the optimization of any underwater camera system working within these waters.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012569
Subject Headings: Oceanographic submersibles--Mathematical models, Image processing--Digital techniques, Optical pattern recognition, Port Everglades (Fort Lauderdale, Fla)
Format: Document (PDF)

Title: System level simulations of an optical character recognition system.
Creator: Phadnis, Mangirish Jayawant., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Optical Character Recognition systems have many applications in today's world of electronic computing. Various software implementations are currently being used. This thesis evolves a massively parallel hardware implementation for the system that is VLSI scaleable and may lead to substantial increase in the processing speed. This system involves various stages for preprocessing and processing of the image implemented with SIMD architecture, using simple processing elements and near neighbor...
Show moreOptical Character Recognition systems have many applications in today's world of electronic computing. Various software implementations are currently being used. This thesis evolves a massively parallel hardware implementation for the system that is VLSI scaleable and may lead to substantial increase in the processing speed. This system involves various stages for preprocessing and processing of the image implemented with SIMD architecture, using simple processing elements and near neighbor communications. The architecture evolved is simulated using the Verilog Hardware Description Language. This project should provide a framework for a massively parallel processing architecture for such systems. It is expected that this project will lead to the design and implementation of a real time system.
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Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/15106
Subject Headings: Optical character recognition devices, Integrated circuits--Very large scale integration, Optical scanners, Image processing--Digital techniques
Format: Document (PDF)

Title: A method to create three-dimensional facial image from two-dimensional facial data set.
Creator: Theerawong, Teerapat., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A method to create 3D-face image using 2D-face images is the objective of this research. The 3D-face image is constructed using a set of 3D-face images of other persons available in a face database. The 3D-face image actually depicts a parameterized form in terms of depth and texture. This concept can be used to facilitate creating a 3D-face image from 2D database. For this purpose, a 3D-face database is first developed. When a 2D-face image is presented to the system, a 3D-face image that...
Show moreA method to create 3D-face image using 2D-face images is the objective of this research. The 3D-face image is constructed using a set of 3D-face images of other persons available in a face database. The 3D-face image actually depicts a parameterized form in terms of depth and texture. This concept can be used to facilitate creating a 3D-face image from 2D database. For this purpose, a 3D-face database is first developed. When a 2D-face image is presented to the system, a 3D-face image that starts with an average 3D-face image (derived from the 3D-face database) is projected onto the 2D-image plane, with necessary rotation, translation, scaling and interpolation. The projected image is then compared with the input image; and, an optimization algorithm is applied to minimize an error index by selecting 3D-depth and texture parameters. Hence, the projected image is derived. Once the algorithm converges, the resulting 3D-depth and the texture parameters can be employed to construct a 3D-face image of the subject photographed in the 2D-images. A merit of this method is that only the depth and texture parameters of the compared images are required to be stored in the database. Such data can be used either for the recreation of a 3D-image of the test subject or for any biometric authentication (based on 3D face recognition). Results from an experimental study presented in the thesis illustrate the effectiveness of the proposed approach, which has applications in biometric authentication and 3D computer graphics areas.
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Date Issued: 2006
PURL: http://purl.flvc.org/fcla/dt/13407
Subject Headings: Image processing--Digital techniques, Computervision, Computer graphics, Three-dimensional display systems, Computer-aided design
Format: Document (PDF)

Title: Mapping urban land cover using multi-scale and spatial autocorrelation information in high resolution imagery.
Creator: Johnson, Brian A., Charles E. Schmidt College of Science, Department of Geosciences
Abstract/Description: Fine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of...
Show moreFine-scale urban land cover information is important for a number of applications, including urban tree canopy mapping, green space analysis, and urban hydrologic modeling. Land cover information has traditionally been extracted from satellite or aerial images using automated image classification techniques, which classify pixels into different categories of land cover based on their spectral characteristics. However, in fine spatial resolution images (4 meters or better), the high degree of within-class spectral variability and between-class spectral similarity of many types of land cover leads to low classification accuracy when pixel-based, purely spectral classification techniques are used. Object-based classification methods, which involve segmenting an image into relatively homogeneous regions (i.e. image segments) prior to classification, have been shown to increase classification accuracy by incorporating the spectral (e.g. mean, standard deviation) and non-spectral (e.g. te xture, size, shape) information of image segments for classification. One difficulty with the object-based method, however, is that a segmentation parameter (or set of parameters), which determines the average size of segments (i.e. the segmentation scale), is difficult to choose. Some studies use one segmentation scale to segment and classify all types of land cover, while others use multiple scales due to the fact that different types of land cover typically vary in size. In this dissertation, two multi-scale object-based classification methods were developed and tested for classifying high resolution images of Deerfield Beach, FL and Houston, TX. These multi-scale methods achieved higher overall classification accuracies and Kappa coefficients than single-scale object-based classification methods., Since the two dissertation methods used an automated algorithm (Random Forest) for image classification, they are also less subjective and easier to apply to other study areas than most existing multi-scale object-based methods that rely on expert knowledge (i.e. decision rules developed based on detailed visual inspection of image segments) for classifying each type of land cover.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342110
Subject Headings: Image processing, Digital techniques, Remote sensing, Mathematics, Remote-sensing images, Computational intelligence, Cities and towns, Remote sensing, Environmental sciences, Remote sensing, Spatial analysis (Statistics)
Format: Document (PDF)

Title: Face Processing Using Mobile Devices.
Creator: James, Jhanon, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Image Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection...
Show moreImage Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection has become a commodity and is now incorporated into simple devices such as digital cameras and smartphones. An iOS app was implemented in Objective-C using Microsoft Cognitive Ser- vices APIs, as a tool for human vision and face processing research. Experimental work on image compression, upside-down orientation, the Thatcher e ect, negative inversion, high frequency, facial artifacts, caricatures and image degradation were completed on the Radboud and 10k US Adult Faces Databases along with other images.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004770, http://purl.flvc.org/fau/fd/FA00004770
Subject Headings: Image processing--Digital techniques., Mobile communication systems., Mobile computing., Artificial intelligence., Human face recognition (Computer science), Computer vision., Optical pattern recognition.
Format: Document (PDF)

Image processing--Digital techniques (21)	+ -
Digital techniques (9)	+ -
Image processing (9)	+ -
Coding theory (4)	+ -
Computer vision (4)	+ -

Pattern recognition systems (4)	+ -
Biometric identification (3)	+ -
Digital video (3)	+ -
Multimedia systems (3)	+ -
Remote sensing (3)	+ -
Security measures (3)	+ -
Computer algorithms (2)	+ -
Computer systems (2)	+ -
Data compression (Telecommunication) (2)	+ -
Data encryption (Computer science) (2)	+ -
Human face recognition (Computer science) (2)	+ -
Human-computer interaction (2)	+ -
Image processing -- Digital techniques (2)	+ -
Imaging systems (2)	+ -
Information storage and retrieval systems (2)	+ -
Mathematical models (2)	+ -
Optical character recognition devices (2)	+ -
Video compression (2)	+ -
Visual perception (2)	+ -
Approximation theory -- Mathematical models (1)	+ -
Artificial intelligence (1)	+ -
Artificial intelligence. (1)	+ -
Bioinformatics (1)	+ -
Cities and towns (1)	+ -
Cluster analysis (1)	+ -

College of Engineering and Computer Science (27)	+ -
Department of Computer and Electrical Engineering and Computer Science (26)	+ -
Florida Atlantic University (26)	+ -
Furht, Borko (5)	+ -
Marques, Oge (4)	+ -

Sudhakar, Raghavan (3)	+ -
Charles E. Schmidt College of Science (2)	+ -
Erdol, Nurgun (2)	+ -
Pandya, Abhijit S. (2)	+ -
BEGUN, RALPH MURRAY. (1)	+ -
Barenholtz, Elan (1)	+ -
Boutros, George. (1)	+ -
Castellanos Jimenez, Ricardo Augusto. (1)	+ -
Center for Complex Systems and Brain Sciences (1)	+ -
Costa, Fabio Morais. (1)	+ -
Department of Geosciences (1)	+ -
Department of Ocean and Mechanical Engineering (1)	+ -
Dong, Xu. (1)	+ -
Frisk, George V. (1)	+ -
Gammack-Clark, James Peter (1)	+ -
Garcia, Ray (1)	+ -
Gibson, Joel (1)	+ -
Glenn, William E. (1)	+ -
Greenberg, Joshua H. (1)	+ -
Guo, Linfeng. (1)	+ -
Hahn, William E. (1)	+ -
Huang, Ziqiang. (1)	+ -
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Johnson, Brian A. (1)	+ -
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