Dynamically Parallel Camshift: Gpu Accelerated Object Tracking In Digital Video,
2016
Eastern Washington University
Dynamically Parallel Camshift: Gpu Accelerated Object Tracking In Digital Video, Matthew J. Perry
EWU Masters Thesis Collection
"The CAMSHIFT algorithm is widely used for tracking dynamically sized and positioned objects in real-time applications. In spite of its extensive study on the platform of sequential CPU, its research on massively parallel Graphical Processing Unit (GPU) platform is quite limited. In this work, we designed and implemented two different parallel algorithms for CAMSHIFT using CUDA. The first design performs calculations on the GPU, but requires iterative data transfers back to the host CPU for condition checking, which bottlenecks the entire program. In the second design, we propose an enhanced parallel reduction-based CAMSHIFT using dynamic parallelism to reduce overhead of …
Press: Personalized Event Scheduling Recommender System (Demonstration),
2016
Singapore Management University
Press: Personalized Event Scheduling Recommender System (Demonstration), Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang
Research Collection School Of Computing and Information Systems
This paper presents a personalized event scheduling recom-mender system, PRESS, for a large conference setting with multiple parallel tracks. PRESS is a mobile application that gathers personalized information from a user and recommends talks/demos to be attend. The input from a user include a list of keyword preferences and (optionally) preferred talks. We use the MALLET topic model package to analyze the set of conference papers and classify them based on automatically identified topics. We propose an algorithm to generate a list of recommended papers based on the user keywords and the MALLET topics. An optimization model is then applied …
Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model,
2016
Singapore Management University
Performance Based Contracting For The Manufacturing Industry By Using Integrated Platform And Dynamic Pricing Model, Lindawati, Aldy Gunawan
Research Collection Lee Kong Chian School Of Business
Although Performance Based Contracting (PBC) concept is not totally new, the PBC adaptation in Industrial Machinery and Components (IMC) manufacturing, which produces high-value and long life machineries, is rather slow and it is done with extra caution. Three main concerns for manufacturers to implement PBC are the investment cost, the maintenance cost and possible revenue loss. To handle these concerns and accelerate the PBC implementation, we propose an integrated platform that consists of three components: dynamic pricing, sensor data feeding and machinery monitoring. We model the dynamic pricing as an optimization problem and propose Genetic Algorithm to solve the problem. …
Battle Bot Ai – Patriot Bot,
2015
California Polytechnic State University, San Luis Obispo
Battle Bot Ai – Patriot Bot, James Johnston
Computer Engineering
An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.
Positive Influence Dominating Set Generation In Social Networks,
2015
Ursinus College
Positive Influence Dominating Set Generation In Social Networks, Akshaye Dhawan, Matthew Rink
Mathematics, Computer Science & Statistics Faculty Publications
Current algorithms in the Positive Influence Dominating Set (PIDS) problem domain are focused on a specific type of PIDS, the Total Positive Influence Dominating Set (TPIDS). We have developed an algorithm specifically targeted towards the non-total type of PIDS. In addition to our new algorithm, we adapted two existing TPIDS algorithms to generate PIDS. We ran simulations for all three algorithms, and our new algorithm consistently generates smaller PIDS than both existing algorithms, with our algorithm generating PIDS approximately 5% smaller than the better of the two existing algorithms.
Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks,
2015
Ursinus College
Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks, Akshaye Dhawan, Michelle Tanco, Aaron Yeiser
Mathematics, Computer Science & Statistics Faculty Publications
A Connected Dominating Set (CDS) of a graph representing a Wireless Sensor Network can be used as a virtual backbone for routing through the network. Since the sensors in the network are constrained by limited battery life, we desire a minimal CDS for the network, a known NP-hard problem. In this paper we present three randomized algorithms for constructing a CDS. We evaluate our algorithms using simulations and compare them to the two-hop K2 algorithm and two other greedy algorithms from the literature. After pruning, the randomized algorithms construct a CDS that are generally equivalent in size to those constructed …
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 …
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 …
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 …
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
School of Computing: 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.
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 …
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 …
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 …
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 …
Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements,
2015
Portland State University
Evaluation Of Data-Path Topologies For Self-Timed Conditional Statements, Navaneeth Prasannakumar Jamadagni
Dissertations and Theses
This research presents a methodology to evaluate data path topologies that implement a conditional statement for an average-case performance that is better than the worst-case performance. A conditional statement executes one of many alternatives depending on how Boolean conditions evaluate to true or false. Alternatives with simple computations take less time to execute. The self-timed designs can exploit the faster executing alternatives and provide an average-case behavior, where the average depends on the frequency of simple and complex computations, and the difference in the completion times of simple and complex computations. The frequency of simple and complex computations depends on …
Tweakable Ciphers: Constructions And Applications,
2015
Portland State University
Tweakable Ciphers: Constructions And Applications, Robert Seth Terashima
Dissertations and Theses
Tweakable ciphers are a building block used to construct a variety of cryptographic algorithms. Typically, one proves (via a reduction) that a tweakable-cipher-based algorithm is about as secure as the underlying tweakable cipher. Hence improving the security or performance of tweakable ciphers immediately provides corresponding benefits to the wide array of cryptographic algorithms that employ them. We introduce new tweakable ciphers, some of which have better security and others of which have better performance than previous designs. Moreover, we demonstrate that tweakable ciphers can be used directly (as opposed to as a building block) to provide authenticated encryption with associated …
