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 …
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 …
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines,
2017
university of south carolina
Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K Sharma
Publications
Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new …
Performance Resilience Analysis Of Dynamic Feedback Controllers For Both Multiplicative And Additive Gain Perturbations,
2017
Marquette University
Performance Resilience Analysis Of Dynamic Feedback Controllers For Both Multiplicative And Additive Gain Perturbations, Fan Feng, Susan C. Schneider, Edwin E. Yaz
Electrical and Computer Engineering Faculty Research and Publications
In this work, a procedure is presented for performance resilience analysis of continuous-time systems controlled by full-order dynamic feedback compensators. The resilience property is defined in terms of defining maximum perturbations on both the controller and observer gains that will maintain controller and observer eigenvalues in disjoint regions in the complex plane so that the closed loop system will sustain certain performance characteristics. The desired performance is characterized by the response speed and magnitude bounds on the response. Therefore, the intersection of two regions are chosen, vertical strips and sector regions, to guarantee upper and lower bounds on the settling …
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.
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 …
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.
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 …
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 …
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 …
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.
Multi-View Face Recognition From Single Rgbd Models Of The Faces,
2017
Purdue University
Multi-View Face Recognition From Single Rgbd Models Of The Faces, Donghun Kim, Bharath Comandur, Henry P. Medeiros, Noha M. Elfiky, Avinash Kak
Electrical and Computer Engineering Faculty Research and Publications
This work takes important steps towards solving the following problem of current interest: Assuming that each individual in a population can be modeled by a single frontal RGBD face image, is it possible to carry out face recognition for such a population using multiple 2D images captured from arbitrary viewpoints? Although the general problem as stated above is extremely challenging, it encompasses subproblems that can be addressed today. The subproblems addressed in this work relate to: (1) Generating a large set of viewpoint dependent face images from a single RGBD frontal image for each individual; (2) using hierarchical approaches based …
Modeling Micro-Porous Surfaces For Secondary Electron Emission Control To Suppress Multipactor,
2017
Air Force Institute of Technology
Modeling Micro-Porous Surfaces For Secondary Electron Emission Control To Suppress Multipactor, J. M. Sattler, Ronald A. Coutu Jr., R. Lake, T. Laurvick, T. Back, S. Fairchild
Electrical and Computer Engineering Faculty Research and Publications
This work seeks to understand how the topography of a surface can be engineered to control secondary electron emission (SEE) for multipactor suppression. Two unique, semi-empirical models for the secondary electron yield (SEY) of a micro-porous surface are derived and compared. The first model is based on a two-dimensional (2D) pore geometry. The second model is based on a three-dimensional (3D) pore geometry. The SEY of both models is shown to depend on two categories of surface parameters: chemistry and topography. An important parameter in these models is the probability of electron emissions to escape the surface pores. This probability …
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 …
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 …
A-Z Database Discovery Using Alma: Eliminate Redundancy And Simplify Your Workflow,
2017
East Tennessee State University
A-Z Database Discovery Using Alma: Eliminate Redundancy And Simplify Your Workflow, Travis Clamon
ETSU Faculty Works
Frustrated by having to maintain an A-Z databases list separately on our library website and in Alma/Primo, East Tennessee State University embarked on a goal to eliminate redundancy by using Alma as our primary source of metadata for eResources. This presentation will cover our entire workflow and the issues we encountered along the way. I'll first go over our process in Alma including MARC record creation, electronic collection setup, and the top level collection module. Next, I'll cover our workflow in Primo including normalization rules, scoping, and PNX display. The last section will cover the Alma API's and how they …
Toward Quality Attribute Driven Approach To Software Architectural Design,
2017
University of North Dakota
Toward Quality Attribute Driven Approach To Software Architectural Design, Payel Bajpayee, Hassan Reza
Computer Science Faculty Publications
It has been well-documented that the software architecture of any system plays a critical role in success or failure of software intensive systems. In this paper, a method has been proposed to evaluate the software architecture’s fitness with respect to key quality attributes for a web-based system. To the end, a comparative analysis based on quality attributes scenarios and tactics is carried out to select an optimal software architecture that meets the system level requirements of a web-based system, namely, Student and Course Evaluation System (SCES). The comparative study was driven by study of quality attributes and tactics with the …
Multi-Bot Easy Control Hierarchy,
2017
Santa Clara University
Multi-Bot Easy Control Hierarchy, Ryan Cooper, Marton Demeter, Jonathan Ho, Alan Nguyen
Computer Science and Engineering Senior Theses
The goal of our project is to create a software architecture that makes it possible to easily control a multi-robot system, as well as seamlessly change control modes during operation. The different control schemes first include the ability to implement on-board and off-board controllers. Second, the commands can specify either actuator level, vehicle level, or fleet level behavior. Finally, motion can be specified by giving a waypoint and time constraint, a velocity and heading, or a throttle and angle. Our code is abstracted so that any type of robot - ranging from ones that use a differential drive set up, …
