Co-Rotational Finite Element Solid Simulation With Collisions, 2015 California Polytechnic State University - San Luis Obispo
Co-Rotational Finite Element Solid Simulation With Collisions, Patrick Riordan
Computer Science and Software Engineering
This paper is a tutorial on how to implement a deformable solid simulation with collisions based off of Matthias Mueller's Real Time Physics Course Notes. It covers the topics continuum mechanics, finite element analysis, implicit Euler integration, and handling collision.
Multiple Instance Fuzzy Inference., 2015 University of Louisville
Multiple Instance Fuzzy Inference., Amine Ben Khalifa
Electronic Theses and Dissertations
A novel fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Fuzzy Inference Systems (MI-FIS). Fuzzy inference is a powerful modeling framework that can handle computing with knowledge uncertainty and measurement imprecision effectively. Fuzzy Inference performs a non-linear mapping from an input space to an output space by deriving conclusions from a set of fuzzy if-then rules and known facts. Rules can be identified from expert knowledge, or learned from data. In multiple instance problems, the training data …
An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, 2015 University of Dayton
An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang
Computer Science Faculty Publications
We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …
Differentially Private Subspace Clustering, 2015 Carnegie Mellon University
Differentially Private Subspace Clustering, Yining Wang, Yu-Xiang Wang, Aarti Singh
Research Collection School Of Computing and Information Systems
Subspace clustering is an unsupervised learning problem that aims at grouping data points into multiple “clusters” so that data points in a single cluster lie approximately on a low-dimensional linear subspace. It is originally motivated by 3D motion segmentation in computer vision, but has recently been generically applied to a wide range of statistical machine learning problems, which often involves sensitive datasets about human subjects. This raises a dire concern for data privacy. In this work, we build on the framework of differential privacy and present two provably private subspace clustering algorithms. We demonstrate via both theory and experiments that …
Disjunctive Answer Set Solvers Via Templates, 2015 Department of Compter Science
Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea
Yuliya Lierler
Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, 2015 Iowa State University
Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, Renliang Gu, Aleksandar Dogandžić
Aleksandar Dogandžić
We develop a projected Nesterov’s proximal-gradient (PNPG) scheme for reconstructing sparse signals from compressive Poisson-distributed measurements with the mean signal intensity that follows an affine model with known intercept. The objective function to be minimized is a sum of convex data fidelity (negative log-likelihood (NLL)) and regularization terms. We apply sparse signal regularization where the signal belongs to a nonempty closed convex set within the domain of the NLL and signal sparsity is imposed using total-variation (TV) penalty. We present analytical upper bounds on the regularization tuning constant. The proposed PNPG method employs projected Nesterov’s acceleration step, function restart, and …
Skeleton Structures And Origami Design, 2015 University of Massachusetts Amherst
Skeleton Structures And Origami Design, John C. Bowers
Doctoral Dissertations
In this dissertation we study problems related to polygonal skeleton structures that have applications to computational origami. The two main structures studied are the straight skeleton of a simple polygon (and its generalizations to planar straight line graphs) and the universal molecule of a Lang polygon. This work builds on results completed jointly with my advisor Ileana Streinu. Skeleton structures are used in many computational geometry algorithms. Examples include the medial axis, which has applications including shape analysis, optical character recognition, and surface reconstruction; and the Voronoi diagram, which has a wide array of applications including geographic information systems …
Extending The Teknomo-Fernandez Background Image Generation Algorithm On The Hsv Colour Space, 2015 Ateneo de Manila University
Extending The Teknomo-Fernandez Background Image Generation Algorithm On The Hsv Colour Space, Patricia Angela R. Abu, Proceso L. Fernandez Jr
Department of Information Systems & Computer Science Faculty Publications
Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strategy to produce a good background image very quickly. A previous study showed that the TF algorithm can be extended from the original 3 frames per tournament (T F 3) to T F 5 and T F 7, resulting in increased accuracies at a cost of increased processing times. In this study, we explore extending the T F 3, …
Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, 2015 Chongqing University of Posts and Telecommunications
Dictionary Pair Learning On Grassmann Manifolds For Image Denoising, Xianhua Zeng, Wei Bian, Wei Liu, Jialie Shen, Dacheng Tao
Research Collection School Of Computing and Information Systems
Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary …
Implementing And Testing A Novel Chaotic Cryptosystem, 2015 Selected Works
Implementing And Testing A Novel Chaotic Cryptosystem, Samuel Jackson, Scott Kerlin, Jeremy Straub
Jeremy Straub
Cryptography in the domain of small satellites is a relatively new area of research. Compared to typical desktop computers, small satellites have limited bandwidth, processing power, and battery power. Many of the current encryption schemes were developed for desktop computers and servers, and as such may be unsuitable for small satellites. In addition, most cryptographic research in the domain of small satellites focuses on hardware solutions, which can be problematic given the limited space requirements of small satellites.
This paper investigates potential software solutions that could be used to encrypt and decrypt data on small satellites and other devices with …
Prediction: The Quintessential Model Validation Test, 2015 Portland State University
Prediction: The Quintessential Model Validation Test, Wayne Wakeland
Systems Science Friday Noon Seminar Series
It is essential to objectively test how well policy models predict real world behavior. The method used to support this assertion involves the review of three SD policy models emphasizing the degree to which the model was able to fit the historical outcome data and how well model-predicted outcomes matched real world outcomes as they unfolded. Findings indicate that while historical model agreement is a favorable indication of model validity, the act of making predictions without knowing the actual data, and comparing these predictions to actual data, can reveal model weaknesses that might be overlooked when all of the available …
Formal Models Of The Extension Activity Of Dna Polymerase Enzymes, 2015 The University of Western Ontario
Formal Models Of The Extension Activity Of Dna Polymerase Enzymes, Srujan Kumar Enaganti
Electronic Thesis and Dissertation Repository
The study of formal language operations inspired by enzymatic actions on DNA is part of ongoing efforts to provide a formal framework and rigorous treatment of DNA-based information and DNA-based computation. Other studies along these lines include theoretical explorations of splicing systems, insertion-deletion systems, substitution, hairpin extension, hairpin reduction, superposition, overlapping concatenation, conditional concatenation, contextual intra- and intermolecular recombinations, as well as template-guided recombination.
First, a formal language operation is proposed and investigated, inspired by the naturally occurring phenomenon of DNA primer extension by a DNA-template-directed DNA polymerase enzyme. Given two DNA strings u and v, where the shorter …
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, 2015 University of Nebraska-Lincoln
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li
CSE Conference and Workshop Papers
In this paper, we introduce a new phylogenetic tree algorithm that generates phylogenetic trees by repeatedly inserting species one-by-one. The incremental phylogenetic tree algorithm can work on proteins or DNA sequences. Computer experiments show that the new algorithm is better than the commonly used UPGMA and Neighbor Joining algorithms.
Computational Approaches For Remote Monitoring Of Symptoms And Activities, 2015 Marquette University
Computational Approaches For Remote Monitoring Of Symptoms And Activities, Ferdaus Kawsar
Dissertations (1934 -)
We now have a unique phenomenon where significant computational power, storage, connectivity, and built-in sensors are carried by many people willingly as part of their life style; two billion people now use smart phones. Unique and innovative solutions using smart phones are motivated by rising health care cost in both the developed and developing worlds. In this work, development of a methodology for building a remote symptom monitoring system for rural people in developing countries has been explored. Design, development, deployment, and evaluation of e-ESAS is described. The system’s performance was studied by analyzing feedback from users. A smart phone …
Modeling Flood Risk For An Urban Cbd Using Ahp And Gis, 2015 Ateneo de Manila University
Modeling Flood Risk For An Urban Cbd Using Ahp And Gis, Proceso L. Fernandez Jr, Generino P. Siddayao, Sony E. Valdez
Department of Information Systems & Computer Science Faculty Publications
The Central Business District (CBD) of a city is the activity center of the city, typically locating the main commercial and cultural establishments, as well as acting as the center point of the city’s transportation network. Flood risk assessment for a CBD is crucial for proper city planning and maintenance. In this study, we model the flood risk for the CBD of Tuguegarao City, which is located in northern Philippines. To accomplish this, we identified important flood-related factors whose data are either easily available or may be collected through some automated process that we developed. We then surveyed experts to …
Functional Requirements Identification Using Item-To-Item Collaborative Filtering, 2015 Ateneo de Manila University
Functional Requirements Identification Using Item-To-Item Collaborative Filtering, Proceso L. Fernandez Jr, Reynald Jay F. Hidalgo
Department of Information Systems & Computer Science Faculty Publications
One of the most difficult tasks in the development of software is the identification of the functional requirements. A well-defined functional requirement will eventually map the success of a software project. A support tool that can recommend candidate functional requirements for a software project being developed will help software engineers to deliver the right software to the clients.
The purpose of this study is to determine whether a collection of previously developed software applications can serve as basis for the development of a model to identify functional requirements of a project to be developed. Completed software project documentations of Master …
The Effectiveness Of Using A Modified “Beat Frequent Pick” Algorithm In The First International Roshambo Tournament, 2015 Ateneo de Manila University
The Effectiveness Of Using A Modified “Beat Frequent Pick” Algorithm In The First International Roshambo Tournament, Proceso L. Fernandez Jr, Sony E. Valdez, Generino P. Siddayao
Department of Information Systems & Computer Science Faculty Publications
In this study, a bot is developed to compete in the first International RoShamBo Tournament test suite. The basic “Beat Frequent Pick (BFP)” algorithm was taken from the supplied test suite and was improved by adding a random choice tailored fit against the opponent's distribution of picks. A training program was also developed that finds the best performing bot variant by changing the bot's behavior in terms of the timing of the recomputation of the pick distribution. Simulation results demonstrate the significantly improved performance of the proposed variant over the original BFP. This indicates the potential of using the core …
Integrating Deep Learning With Correlation-Based Multimedia Semantic Concept Detection, 2015 Florida International University
Integrating Deep Learning With Correlation-Based Multimedia Semantic Concept Detection, Hsin-Yu Ha
FIU Electronic Theses and Dissertations
The rapid advances in technologies make the explosive growth of multimedia data possible and available to the public. Multimedia data can be defined as data collection, which is composed of various data types and different representations. Due to the fact that multimedia data carries knowledgeable information, it has been widely adopted to different genera, like surveillance event detection, medical abnormality detection, and many others. To fulfil various requirements for different applications, it is important to effectively classify multimedia data into semantic concepts across multiple domains. In this dissertation, a correlation-based multimedia semantic concept detection framework is seamlessly integrated with the …
A Study Of Pseudo-Periodic And Pseudo-Bordered Words For Functions Beyond Identity And Involution, 2015 The University of Western Ontario
A Study Of Pseudo-Periodic And Pseudo-Bordered Words For Functions Beyond Identity And Involution, Manasi Kulkarni
Electronic Thesis and Dissertation Repository
Periodicity, primitivity and borderedness are some of the fundamental notions in combinatorics on words. Motivated by the Watson-Crick complementarity of DNA strands wherein a word (strand) over the DNA alphabet \{A, G, C, T\} and its Watson-Crick complement are informationally ``identical", these notions have been extended to consider pseudo-periodicity and pseudo-borderedness obtained by replacing the ``identity" function with ``pseudo-identity" functions (antimorphic involution in case of Watson-Crick complementarity). For a given alphabet $\Sigma$, an antimorphic involution $\theta$ is an antimorphism, i.e., $\theta(uv)=\theta(v) \theta(u)$ for all $u,v \in \Sigma^{*}$ and an involution, i.e., $\theta(\theta(u))=u$ for all $u \in \Sigma^{*}$. In this thesis, …
Algorithms For Peptide Identification From Mixture Tandem Mass Spectra, 2015 The University of Western Ontario
Algorithms For Peptide Identification From Mixture Tandem Mass Spectra, Yi Liu
Electronic Thesis and Dissertation Repository
The large amount of data collected in an mass spectrometry experiment requires effective computational approaches for the automated analysis of those data. Though extensive research has been conducted for such purpose by the proteomics community, there are still remaining challenges, among which, one particular challenge is that the identification rate of the MS/MS spectra collected is rather low. One significant reason that contributes to this situation is the frequently observed mixture spectra, which result from the concurrent fragmentation of multiple precursors in a single MS/MS spectrum. However, nearly all the mainstream computational methods still take the assumption that the acquired …