Key Inference From Irish Traditional Music Scores And Recordings,
2017
Technological University Dublin
Key Inference From Irish Traditional Music Scores And Recordings, Pierre Beauguitte, Bryan Duggan, John D. Kelleher
Conference papers
The aim of this paper is to present techniques and results for identifying the key of Irish traditional music melodies, or tunes. Several corpora are used, consisting of both symbolic and audio representations. Monophonic and heterophonic recordings are present in the audio datasets. Some particularities of Irish traditional music are discussed, notably its modal nature. New key-profiles are defined, that are better suited to Irish music.
Development Of Kinematic Templates For Automatic Pronunciation Assessment Using Acoustic-To-Articulatory Inversion,
2017
Marquette University
Development Of Kinematic Templates For Automatic Pronunciation Assessment Using Acoustic-To-Articulatory Inversion, Deriq K. Jones
Master's Theses (2009 -)
Computer-aided pronunciation training (CAPT) is a subcategory of computer-aided language learning (CALL) that deals with the correction of mispronunciation during language learning. For a CAPT system to be effective, it must provide useful and informative feedback that is comprehensive, qualitative, quantitative, and corrective. While the majority of modern systems address the first 3 aspects of feedback, most of these systems do not provide corrective feedback. As part of the National Science Foundation (NSF) funded study “RI: Small: Speaker Independent Acoustic-Articulator Inversion for Pronunciation Assessment”, the Marquette Speech and Swallowing Lab and Marquette Speech and Signal Processing Lab are conducting a …
Deep Neural Networks As Time Series Forecasters Of Energy Demand,
2017
Marquette University
Deep Neural Networks As Time Series Forecasters Of Energy Demand, Gregory Merkel
Master's Theses (2009 -)
Short-term load forecasting is important for the day-to-day operation of natural gas utilities. Traditionally, short-term load forecasting of natural gas is done using linear regression, autoregressive integrated moving average models, and artificial neural networks. Many purchasing and operating decisions are made using these forecasts, and there can be high cost to both natural gas utilities and their customers if the short-term load forecast is inaccurate. Therefore, the GasDay lab continues to explore new ways to make better forecasts. Recently, deep neural networks (DNNs) have emerged as a powerful tool in machine learning problems. DNNs have been shown to greatly outperform …
Querying And Visualization Of Moving Objects Using Constraint Databases,
2017
University of Nebraska - Lincoln
Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …
Investigating Diversity In Open Multiagent Team Formation,
2017
University of Nebraska-Lincoln
Investigating Diversity In Open Multiagent Team Formation, Pooja Ahuja
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Team formation is the most rudimentary form of interactions in distributed AI and multiagent systems as it allows coherent collections of agents to work together in a beneficial manner towards a common goal of interest. Basically, individual expertise are assembled together in an additive fashion for accomplishing tasks together. A plethora of the related studies found in the literature often make several unrealistic assumptions such as coordination amongst the agents, or agents having knowledge of the whole environment, or agents and/or tasks are of the same kind, or a static environment setting. Against this background, we argue that there are …
Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection,
2017
Old Dominion University
Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee
Electrical & Computer Engineering Theses & Dissertations
Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …
Design Of A Virtual Laboratory For Automation Control,
2017
Old Dominion University
Design Of A Virtual Laboratory For Automation Control, Zelin Zhu
Computational Modeling & Simulation Engineering Theses & Dissertations
In the past, only students who studied on campus were able to access laboratory equipment in traditional lab courses; distance learning students, enrolled in online courses, were at a disadvantage for they could learn basic lab experiment principles but could never experience hands-on learning. Modeling and simulation can be a powerful tool for generating virtual laboratories for distance learning students. This thesis describes the design and development of a virtual laboratory for automation control using mechanical, electrical, and pneumatic components for an automation and control course at Old Dominion University. This virtual laboratory application was implemented for two platforms — …
Mining Capstone Project Wikis For Knowledge Discovery,
2017
Singapore Management University
Mining Capstone Project Wikis For Knowledge Discovery, Swapna Gottipati, Venky Shankararaman, Melvrivk Goh
Research Collection School Of Computing and Information Systems
Wikis are widely used collaborative environments as sources of information and knowledge. The facilitate students to engage in collaboration and share information among members and enable collaborative learning. In particular, Wikis play an important role in capstone projects. Wikis aid in various project related tasks and aid to organize information and share. Mining project Wikis is critical to understand the students learning and latest trends in industry. Mining Wikis is useful to educationists and academicians for decision-making about how to modify the educational environment to improve student's learning. The main challenge is that the content or data in project Wikis …
Motion Planning For Simple Two-Wheeled Robots,
2017
Loyola University Chicago
Motion Planning For Simple Two-Wheeled Robots, Ronald I. Greenberg, Jeffery M. Karp
Computer Science: Faculty Publications and Other Works
This paper considers various simple ways of navigating in a 2-dimensianal territory with a two-wheeled robot of a type typical in educational robotics. We determine shortest paths under various modes of operation and compare.
Attribute-Based Encryption With Expressive And Authorized Keyword Search,
2017
Singapore Management University
Attribute-Based Encryption With Expressive And Authorized Keyword Search, Hui Cui, Robert H. Deng, Joseph K. Liu, Yingjiu Li
Research Collection School Of Computing and Information Systems
To protect data security and privacy in cloud storage systems, a common solution is to outsource data in encrypted forms so that the data will remain secure and private even if storage systems are compromised. The encrypted data, however, must be pliable to search and access control. In this paper, we introduce a notion of attribute-based encryption with expressive and authorized keyword search (ABE-EAKS) to support both expressive keyword search and fine-grained access control over encrypted data in the cloud. In ABE-EAKS, every data user is associated with a set of attributes and is issued a private attribute-key corresponding to …
Cyber Foraging: Fifteen Years Later,
2017
Singapore Management University
Cyber Foraging: Fifteen Years Later, Rajesh Krishna Balan, Jason Flinn
Research Collection School Of Computing and Information Systems
Revisiting Mahadev Satyanarayanan's original vision of cyber foraging and reflecting on the last 15 years of related research, the authors discuss the major accomplishments achieved as well as remaining challenges. They also look to current and future applications that could provide compelling application scenarios for making cyber foraging a widely deployed technology. This article is part of a special issue on pervasive computing revisited.
Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism,
2017
Singapore Management University
Discovering Newsworthy Themes From Sequenced Data: A Step Towards Computational Journalism, Qi Fan, Yuchen Li, Dongxiang Zhang, Kian-Lee Tan Tan
Research Collection School Of Computing and Information Systems
Automatic discovery of newsworthy themes from sequenced data can relieve journalists from manually poring over a large amount of data in order to find interesting news. In this paper, we propose a novel k -Sketch query that aims to find k striking streaks to best summarize a subject. Our scoring function takes into account streak strikingness and streak coverage at the same time. We study the k -Sketch query processing in both offline and online scenarios, and propose various streak-level pruning techniques to find striking candidates. Among those candidates, we then develop approximate methods to discover the k most representative …
Perception And Reality: Measuring Digital Skills In Singapore,
2017
Singapore Management University
Perception And Reality: Measuring Digital Skills In Singapore, Swapna Gottipati
Research Collection School Of Computing and Information Systems
ICDL Asia carried out a digital literacy study in Singapore, looking at an essential skill for everyday life. The goal of the study was to discover the digital skills gaps among young people in Singapore. Singapore is considered to be a digitally advanced country where young people have access to the latest technology and gadgets. At the same time, it is imperative for young people to possess relevant digital skills for a future-ready and healthy economy. The studies consisted of two key parts: self-assessment and practical assessment of digital skills. Our findings show that, though the digital native fallacy exists …
Gms: Grid-Based Motion Statistics For Fast, Ultra-Robust Feature Correspondence,
2017
Singapore Management University
Gms: Grid-Based Motion Statistics For Fast, Ultra-Robust Feature Correspondence, Jiawang Bian, Wen-Yan Lin, Matsushita Yasuyuki, Sai-Kit Yeung, Tan-Dat Nguyen, Ming-Ming Cheng
Research Collection School Of Computing and Information Systems
Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smoothness as the statistical likelihood of a certain number of matches in a region. GMS enables translation of high match numbers into high match quality. This provides a real-time, ultra-robust correspondence system. Evaluation on videos, with low textures, blurs and wide-baselines show GMS consistently out-performs other real-time matchers and can achieve parity with more sophisticated, much slower techniques.
Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct,
2017
University of Dayton
Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay
Russell C. Hardie
Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii) …
On The Simulation And Mitigation Of Anisoplanatic Optical Turbulence For Long Range Imaging,
2017
University of Dayton
On The Simulation And Mitigation Of Anisoplanatic Optical Turbulence For Long Range Imaging, Russell C. Hardie, Daniel A. Lemaster
Russell C. Hardie
We describe a numerical wave propagation method for simulating long range imaging of an extended scene under anisoplanatic conditions. Our approach computes an array of point spread functions (PSFs) for a 2D grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. To validate the simulation we compare simulated outputs with the theoretical anisoplanatic tilt correlation and differential tilt variance. This is in addition to comparing the long- and short-exposure PSFs, and isoplanatic angle. Our validation analysis shows an …
Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory,
2017
Air Force Research Laboratory
Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory, Daniel A. Lemaster, Russell C. Hardie, Szymon Gladysz, Matthew D. Howard, Michael Armand Rucci, Matthew E. Trippel, Jonathan D. Power, Barry K. Karch
Russell C. Hardie
Differential tilt variance is a useful metric for interpreting the distorting effects of turbulence in incoherent imaging systems. In this paper, we compare the theoretical model of differential tilt variance to simulations. Simulation is based on a Monte Carlo wave optics approach with split step propagation. Results show that the simulation closely matches theory. The results also show that care must be taken when selecting a method to estimate tilts.
Chaos-Based Cryptography For Cloud Computing,
2017
Technological University Dublin
Chaos-Based Cryptography For Cloud Computing, Paul Tobin, Lee Tobin, Michael Mckeever, Jonathan Blackledge
Conference papers
Cloud computing and poor security issues have quadrupled over the last six years and with the alleged presence of backdoors in common encryption ciphers, has created a need for personalising the encryption process by the client. In 2007, two Microsoft employees gave a presentation ``On the Possibility of a backdoor in the NIST SP800-90 Dual Elliptic Curve Pseudo Random Number Generators'' and was linked in 2013 by the New York Times with notes leaked by Edward Snowden. This confirmed backdoors were placed, allegedly, in a number of encryption systems by the National Security Agency, which if true creates an urgent …
Large-Scale Flexible Membrane For Automatic Strain Monitoring Of Transportation Infrastructure,
2017
Iowa State University
Large-Scale Flexible Membrane For Automatic Strain Monitoring Of Transportation Infrastructure, Simon Laflamme, Venkata D. Kolipara, Hussam S. Saleem, Randall L. Geiger
Randall Geiger
Structural Health Monitoring (SHM) of transportation infrastructures is a complex task, typically conducted by visual inspection due to the technical and economical constrains of existing health monitoring technologies. It results that health monitoring is highly dependent on scheduling and on the judgment of the inspectors, which can be costly and ineffective. Thus, it is fundamental to automate the SHM process to allow timely inspection, maintenance, and management of transportation infrastructure. The authors propose a flexible membrane that can be deployed over large surfaces, at low cost, for automatic and continuous monitoring of strains. The membrane, termed sensing skin, is constituted …
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice,
2017
Technological University Dublin
One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge
Conference papers
In this paper, we examine the design and application of a one-time pad encryption system for protecting data stored in the Cloud. Personalising security using a one-time pad generator at the client-end protects data from break-ins, side-channel attacks and backdoors in public encryption algorithms. The one-time pad binary sequences were obtained from modified analogue chaos oscillators initiated by noise and encoded client data locally. Specific ``one-to-Cloud'' storage applications returned control back to the end user but without the key distribution problem normally associated with one-time pad encryption. Development of the prototype was aided by ``Virtual Prototyping'' in the latest version …
