Automated Prediction Of Glasgow Outcome Scale For Traumatic Brain Injury,
2014
Singapore Management University
Automated Prediction Of Glasgow Outcome Scale For Traumatic Brain Injury, Bolan Su, Thien Anh Dinh, A. K. Ambastha, Tianxia Gong, Tomi Silander, Shijian Lu, C. C. Tchoyoson Lim, Boon Chuan Pang, Cheng Kiang Lee, Tze-Yun Leong, Chew Lim Tan
Research Collection School Of Computing and Information Systems
Clinical features found in brain CT scan images are widely used in traumatic brain injury (TBI) as indicators for Glasgow Outcome Scale (GOS) prediction. However, due to the lack of automated methods to measure and quantify the CT scan image features, the computerized prediction of GOS in TBI has not been well studied. This paper introduces an automated GOS prediction system for traumatic brain CT images. Different from most existing systems that perform the prognosis based on pre-processed data, our system directly works on brain CT scan images based on the image features. Our system can also be extended to …
A Fast Decomposition Approach For Traffic Control,
2014
Singapore Management University
A Fast Decomposition Approach For Traffic Control, Xiaocheng Tang, Sébastien Blandin, Laura Wynter
Research Collection School Of Computing and Information Systems
Real-time road traffic control has been the subject of active research efforts for more than fifty years. In recent years, however, the convergence of ubiquitous sensing with seamless communication technologies has motivated the development of more computationally efficient control methods, able to operate in real-time in a live environment. In this work, we present a fast decomposition method for network optimization problems, with application to real-time traffic control. Our approach is based on a nonlinear programming formulation of the network control problem and consists of an alternating directions method using forward numerical simulation in place of one of the optimization …
Seismic Imaging Of Mantle Transition Zone Discontinuities Beneath The Northern Red Sea And Adjacent Areas,
2014
Missouri University of Science and Technology
Seismic Imaging Of Mantle Transition Zone Discontinuities Beneath The Northern Red Sea And Adjacent Areas, A. A. Mohamed, Stephen S. Gao, A. A. Elsheikh, Kelly H. Liu, Youqiang Yu, R. E. Fat-Helbary
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The dramatic asymmetry in terms of surface elevation, Cenozoic volcanisms and earthquake activity across the Red Sea is an enigmatic issue in global tectonics, partially due to the unavailability of broad-band seismic data on the African Plate adjacent to the Red Sea. Here, we report the first comprehensive image of the mantle transition zone (MTZ) discontinuities using data from the Egyptian National Seismic Network, and compare the resulting depths of the 410 and 660-km discontinuities with those observed on the Arabian side. Our results show that when a standard earth model is used for time-to-depth conversion, the resulting depth of …
Software Porting Of A 3d Reconstruction Algorithm To Razorcam Embedded System On Chip,
2014
University of Arkansas, Fayetteville
Software Porting Of A 3d Reconstruction Algorithm To Razorcam Embedded System On Chip, Kevin Curtis Gunn
Graduate Theses and Dissertations
A method is presented to calculate depth information for a UAV navigation system from Keypoints in two consecutive image frames using a monocular camera sensor as input and the OpenCV library. This method was first implemented in software and run on a general-purpose Intel CPU, then ported to the RazorCam Embedded Smart-Camera System and run on an ARM CPU onboard the Xilinx Zynq-7000. The results of performance and accuracy testing of the software implementation are then shown and analyzed, demonstrating a successful port of the software to the RazorCam embedded system on chip that could potentially be used onboard a …
Theoretical/Experimental Comparison Of Deep Tunneling Decay Of Quasi-Bound H(D)Oco To H(D) + Co₂,
2014
Missouri University of Science and Technology
Theoretical/Experimental Comparison Of Deep Tunneling Decay Of Quasi-Bound H(D)Oco To H(D) + Co₂, Albert F. Wagner, Richard Dawes, Robert Continetti, Hua Guo
Chemistry Faculty Research & Creative Works
The measured H(D)OCO survival fractions of the photoelectron-photofragment coincidence experiments by the Continetti group are qualitatively reproduced by tunneling calculations to H(D) + CO2 on several recent ab initio potential energy surfaces for the HOCO system. the tunneling calculations involve effective one-dimensional barriers based on steepest descent paths computed on each potential energy surface. the resulting tunneling probabilities are converted into H(D)OCO survival fractions using a model developed by the Continetti group in which every oscillation of the H(D)-OCO stretch provides an opportunity to tunnel. Four different potential energy surfaces are examined with the best qualitative agreement with experiment …
Mantle Transition Zone Discontinuities Beneath The Contiguous United States,
2014
Missouri University of Science and Technology
Mantle Transition Zone Discontinuities Beneath The Contiguous United States, Stephen S. Gao, Kelly H. Liu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Using over 310,000 high-quality radial receiver functions recorded by the USArray and other seismic stations in the contiguous United States, the depths of the 410 km and 660 km discontinuities (d410 and d660) are mapped in over 1,000 consecutive overlapping circles with a radius of 1⁰. The average mantle transition zone (MTZ) thickness for both the western and central/eastern U.S. is within 3 km from the global average of 250 km, suggesting an overall normal MTZ temperature beneath both areas. The Pacific Coast Ranges and the southern Basin and Range Province are underlain by a depressed d410, indicating higher-than-normal temperature …
Effect Of The Center-Of-Mass Approximation On The Scaling Of Electron-Capture Fully Differential Cross Sections,
2014
Missouri University of Science and Technology
Effect Of The Center-Of-Mass Approximation On The Scaling Of Electron-Capture Fully Differential Cross Sections, A. L. Harris, Don H. Madison
Physics Faculty Research & Creative Works
We present results for p+He single electron capture and transfer with target excitation using the first Born approximation. The effect of approximating the center of mass of the helium atom and outgoing hydrogen atom at the respective nuclei is explored. Semianalytical results are compared for the calculations with and without the approximation, and it is shown that one must properly account for the center of mass of the atoms. It is also shown that this approximation is the result of the apparent v4 scaling that was previously observed with the four-body transfer with target excitation model.
Communication: Rigorous Quantum Dynamics Of O + O₂ Exchange Reactions On An Ab Initio Potential Energy Surface Substantiate The Negative Temperature Dependence Of Rate Coefficients,
2014
Missouri University of Science and Technology
Communication: Rigorous Quantum Dynamics Of O + O₂ Exchange Reactions On An Ab Initio Potential Energy Surface Substantiate The Negative Temperature Dependence Of Rate Coefficients, Yaqin Li, Zhigang Sun, Bin Jiang, Daiqian Xie, Richard Dawes, Hua Guo
Chemistry Faculty Research & Creative Works
The kinetics and dynamics of several O + O2 isotope exchange reactions have been investigated on a recently determined accurate global O3 potential energy surface using a time-dependent wave packet method. The agreement between calculated and measured rate coefficients is significantly improved over previous work. More importantly, the experimentally observed negative temperature dependence of the rate coefficients is for the first time rigorously reproduced theoretically. This negative temperature dependence can be attributed to the absence in the new potential energy surface of a submerged "reef" structure, which was present in all previous potential energy surfaces. In addition, contributions …
Direct Neighbor Search,
2014
Singapore Management University
Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …
Online Multiple Kernel Regression,
2014
Singapore Management University
Online Multiple Kernel Regression, Doyen Sahoo, Steven C. H. Hoi, Bin Li
Research Collection School Of Computing and Information Systems
Kernel-based regression represents an important family of learning techniques for solving challenging regression tasks with non-linear patterns. Despite being studied extensively, most of the existing work suffers from two major drawbacks: (i) they are often designed for solving regression tasks in a batch learning setting, making them not only computationally inefficient and but also poorly scalable in real-world applications where data arrives sequentially; and (ii) they usually assume a fixed kernel function is given prior to the learning task, which could result in poor performance if the chosen kernel is inappropriate. To overcome these drawbacks, this paper presents a novel …
Diversity-Oriented Bi-Objective Hyper-Heuristics For Patrol Scheduling,
2014
Singapore Management University
Diversity-Oriented Bi-Objective Hyper-Heuristics For Patrol Scheduling, Mustafa Misir, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The patrol scheduling problem is concerned with assigning security teams to different stations for distinct time intervals while respecting a limited number of contractual constraints. The objective is to minimise the total distance travelled while maximising the coverage of the stations with respect to their security requirement levels. This paper introduces a hyper-heuristic strategy focusing on generating diverse solutions for a bi-objective patrol scheduling problem. While a variety of hyper-heuristics have been applied to a large suite of problem domains usually in the form of single-objective optimisation, we suggest an alternative approach for solving the patrol scheduling problem with two …
Understanding The Paradigm Shift To Computational Social Science In The Presence Of Big Data,
2014
Singapore Management University
Understanding The Paradigm Shift To Computational Social Science In The Presence Of Big Data, Ray M. Chang, Robert J. Kauffman, Young Ok Kwon
Research Collection School Of Computing and Information Systems
The era of big data has created new opportunities for researchers to achieve high relevance and impact amid changes and transformations in how we study social science phenomena. With the emergence of new data collection technologies, advanced data mining and analytics support, there seems to be fundamental changes that are occurring with the research questions we can ask, and the research methods we can apply. The contexts include social networks and blogs, political discourse, corporate announcements, digital journalism, mobile telephony, home entertainment, online gaming, financial services, online shopping, social advertising, and social commerce. The changing costs of data collection and …
Structure Preserving Large Imagery Reconstruction,
2014
University of Dayton
Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz
Computer Science Faculty Publications
With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Furthermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image …
Improving Fmri Analysis And Mr Reconstruction With The Incorporation Of Mr Relaxivities And Correlation Effect Examination,
2014
Marquette University
Improving Fmri Analysis And Mr Reconstruction With The Incorporation Of Mr Relaxivities And Correlation Effect Examination, Meryem Muge Karaman
Dissertations (1934 -)
Functional magnetic resonance imaging (fMRI) and functional connectivity MRI (fcMRI) use the physical principles of nuclear MR to provide high resolution representations of brain activity and connectivity. As the fMRI and fcMRI signals are detected from the excited hydrogen atoms in a magnetic field, the acquired data is determined by the underlying physical processes, such as the MR relaxivities. In fMRI and fcMRI, the Fourier encoded frequency space measurements are reconstructed into brain images, then spatiotemporal processing operations are applied before computing the brain activation and connectivity statistics. This dissertation seeks to utilize the magnetic resonance (MR) relaxivities at different …
Learning Relative Similarity By Stochastic Dual Coordinate Ascent,
2014
Nanyang Technological University
Learning Relative Similarity By Stochastic Dual Coordinate Ascent, Pengcheng Wu, Ding Yi, Peilin Zhao, Chunyan Miao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Learning relative similarity from pairwise instances is an important problem in machine learning and has a wide range of applications. Despite being studied for years, some existing methods solved by Stochastic Gradient Descent (SGD) techniques generally suffer from slow convergence. In this paper, we investigate the application of Stochastic Dual Coordinate Ascent (SDCA) technique to tackle the optimization task of relative similarity learning by extending from vector to matrix parameters. Theoretically, we prove the optimal linear convergence rate for the proposed SDCA algorithm, beating the well-known sublinear convergence rate by the previous best metric learning algorithms. Empirically, we conduct extensive …
Manifold Learning For Jointly Modeling Topic And Visualization,
2014
Singapore Management University
Manifold Learning For Jointly Modeling Topic And Visualization, Tuan Minh Van Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Classical approaches to visualization directly reduce a document's high-dimensional representation into visualizable two or three dimensions, using techniques such as multidimensional scaling. More recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. We call the latter semantic visualization problem, as it seeks to jointly model topic and visualization. While previous approaches aim to preserve the global consistency, they do not consider the local consistency in terms of the intrinsic geometric structure of the document manifold. We therefore propose an unsupervised probabilistic model, called Semafore, which aims to …
Rare Regions And Griffiths Singularities At A Clean Critical Point: The Five-Dimensional Disordered Contact Process,
2014
Missouri University of Science and Technology
Rare Regions And Griffiths Singularities At A Clean Critical Point: The Five-Dimensional Disordered Contact Process, Thomas Vojta, John Igo, José A. Hoyos
Physics Faculty Research & Creative Works
We investigate the nonequilibrium phase transition of the disordered contact process in five space dimensions by means of optimal fluctuation theory and Monte Carlo simulations. We find that the critical behavior is of mean-field type, i.e., identical to that of the clean five-dimensional contact process. It is accompanied by off-critical power-law Griffiths singularities whose dynamical exponent z' saturates at a finite value as the transition is approached. These findings resolve the apparent contradiction between the Harris criterion, which implies that weak disorder is renormalization-group irrelevant, and the rare-region classification, which predicts unconventional behavior. We confirm and illustrate our theory by …
Predicting The Popularity Of Web 2.0 Items Based On User Comments,
2014
National University of Singapore
Predicting The Popularity Of Web 2.0 Items Based On User Comments, Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama
Research Collection School Of Computing and Information Systems
In the current Web 2.0 era, the popularity of Web resources fluctuates ephemerally, based on trends and social interest. As a result, content-based relevance signals are insufficient to meet users' constantly evolving information needs in searching for Web 2.0 items. Incorporating future popularity into ranking is one way to counter this. However, predicting popularity as a third party (as in the case of general search engines) is difficult in practice, due to their limited access to item view histories. To enable popularity prediction externally without excessive crawling, we propose an alternative solution by leveraging user comments, which are more accessible …
Soml: Sparse Online Metric Learning With Application To Image Retrieval,
2014
Chinese Academy of Sciences
Soml: Sparse Online Metric Learning With Application To Image Retrieval, Xingyu Gao, Steven C. H. Hoi, Yongdong Zhang, Ji Wan, Jintao Li
Research Collection School Of Computing and Information Systems
Image similarity search plays a key role in many multimedia applications, where multimedia data (such as images and videos) are usually represented in high-dimensional feature space. In this paper, we propose a novel Sparse Online Metric Learning (SOML) scheme for learning sparse distance functions from large-scale high-dimensional data and explore its application to image retrieval. In contrast to many existing distance metric learning algorithms that are often designed for low-dimensional data, the proposed algorithms are able to learn sparse distance metrics from high-dimensional data in an efficient and scalable manner. Our experimental results show that the proposed method achieves better …
Evidence For Magnetic Clusters In Ni₁₋ₓvₓ Close To The Quantum Critical Concentration,
2014
Missouri University of Science and Technology
Evidence For Magnetic Clusters In Ni₁₋ₓvₓ Close To The Quantum Critical Concentration, R. Wang, S. Ubaid-Kassis, A. Schroeder, P. J. Baker, F. L. Pratt, S. J. Blundell, T. Lancaster, I. Franke, J. S. Möller, Thomas Vojta
Physics Faculty Research & Creative Works
The d-metal alloy Ni1-xVx undergoes a quantum phase transition from a ferromagnetic ground state to a paramagnetic ground state as the vanadium concentration x is increased. We present magnetization, ac-susceptibility and muon-spin relaxation data at several vanadium concentrations near the critical concentration xc ~ 11.6 % at which the onset of ferromagnetic order is suppressed to zero temperature. Below xc, the muon data reveal a broad magnetic field distribution indicative of a long-range ordered ferromagnetic state with spatial disorder. We show evidence of magnetic clusters in the ferromagnetic phase and close to the phase …
