Physical Sciences and Mathematics Commons^™

Valuations Of Possible States (Vps): A Unifying Quantitative Framework For Evaluating Privacy In Collaboration, Rajiv T. Maheswaran, Jonathan Pearce, Pradeep Varakantham, Emma Bowring, Milind Tambe

Research Collection School Of Computing and Information Systems

For agents deployed in real-world settings, such as businesses, universities and research laboratories, it is critical that agents protect their individual users’ privacy when interacting with others entities. Indeed, privacy is recognized as a key motivating factor in design of several multiagent algorithms, such as distributed constraint optimization (DCOP) algorithms. Unfortunately, rigorous and general quantitative metrics for analysis and comparison of such multiagent algorithms with respect to privacy loss are lacking. This paper takes a key step towards developing a general quantitative model from which one can analyze and generate metrics of privacy loss by introducing the VPS (Valuations of …

Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Shih-Fen Cheng, Rahul Suri

Research Collection School Of Computing and Information Systems

To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated local-effect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity.

Social Network Discovery By Mining Spatio-Temporal Events, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang, Teck-Tim Tan

Research Collection School Of Computing and Information Systems

Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals …

Comparing High-Order Boolean Features, Adam Drake, Dan A. Ventura

Faculty Publications

Many learning algorithms attempt, either explicitly or implicitly, to discover useful high-order features. When considering all possible functions that could be encountered, no particular type of high-order feature should be more useful than any other. However, this paper presents arguments and empirical results that suggest that for the learning problems typically encountered in practice, some high-order features may be more useful than others.

Effectively Using Recurrently-Connected Spiking Neural Networks, Eric Goodman, Dan A. Ventura

Faculty Publications

Recurrently-connected spiking neural networks are difficult to use and understand because of the complex nonlinear dynamics of the system. Through empirical studies of spiking networks, we deduce several principles which are critical to success. Network parameters such as synaptic time delays and time constants and the connection probabilities can be adjusted to have a significant impact on accuracy. We show how to adjust these parameters to fit the type of problem.

Time Invariance And Liquid State Machines, Eric Goodman, Dan A. Ventura

Faculty Publications

Time invariant recognition of spatiotemporal patterns is a common task of signal processing. Liquid state machines (LSMs) are a paradigm which robustly handle this type of classification. Using an artificial dataset with target pattern lengths ranging from 0.1 to 1.0 seconds, we train an LSM to find the start of the pattern with a mean absolute error of 0.18 seconds. Also, LSMs can be trained to identify spoken digits, 1-9, with an accuracy of 97.6%, even with scaling by factors ranging from 0.5 to 1.5.

A Late Devonian Isoetalean Lycopsid, Otzinachsonia Beerboweri Gen. Et Sp Nov., From North-Central Pennsylvania, Usa, Walter L. Cressler, H W. Pfefferkorn

Earth & Space Sciences Faculty Publications

No abstract provided.

Promoting Learning Through Peer Group Work, Christine O'Connor, Renli Ma

Conference Papers

The session aimed to help the Summer School participants develop tasks and assessment strategies of peer group work in their own teaching.

Group Key Distribution Via Local Collaboration In Wireless Sensor Networks, Anuj Chadha

Computer Science and Engineering Theses

Wireless sensor networks have been recognized as one of the most important technologies in the networking world. Security of sensor networks is one of the major concerns today. To this end, a whole suite of protocols have been designed to provide various security features which includes key management. This thesis covers the issue of group key management in wireless sensor networks. Traditional cryptographic techniques can be used to provide communication privacy and integrity, but do not provide scalable solutions to group key management. A group key management scheme for sensor networks has been discussed that targets at fast response to …

Distributed Streaming For Video On Demand, Shraddha Rumade

Computer Science and Engineering Theses

With the advent of digital media, implementing reliable Video on Demand (VoD) systems over the best effort Internet is a potential issue. Distributed streaming for Video on Demand presents a combination of two techniques. The first being Distributed Video Streaming using Multicast (DVSM) [1] involves video streaming from multiple servers to overcome path congestion. The second technique, Asynchronous Hybrid mechanism for Video on Demand [2] implements segmentation-based periodic broadcast to effectively share network bandwidth. In this work we aim at providing path diversity of multiple senders and maximizing bandwidth sharing via multicast. We exploit alternate paths in case of congestion …

Fire Retardancy Of Vinyl Ester Nanocomposites: Synergy With Phosphorus-Based Fire Retardants, Grace Chigwada, Panchatapa Jash, David D. Jiang, Charles A. Wilkie

Chemistry Faculty Research and Publications

Vinyl ester (PVE) nanocomposites were prepared using both clay and polyhedral oligosilsesquioxanes (POSS) as the nano-dimensional material. From cone calorimetric data, it was shown that both POSS and clay affect the flammability of the nanocomposites to the same extent. To improve on the flame retardancy, the nanocomposites were combined with phosphorous-containing fire retardants (FRs) and the result compared to the benchmark halogen-containing system. The use of the cone calorimeter to investigate the fire properties of these nanocomposites showed a great reduction in peak heat release rate (PHRR) in the presence of phosphate and slight improvements in average mass loss rate …

Middleware Architecture For Evaluation And Selection Of 3rd Party Web Services For Service Providers, Dipanjan Chakraborty, Suraj K. Jaiswal, Archan Misra, Amit A. Nanavati

Research Collection School Of Computing and Information Systems

This paper presents an architecture to facilitate efficient evaluation and selection of 3rd party Web services for service providers. Most service provider architectures have primarily focused on providing Web service front ends to legacy systems, aggregating and delivering services via workflows. These architectures primarily considered static business contracts between the service provider and its (Web-service enabled) business partners. This approach makes these architectures inflexible to variations in business requirement, partners' performance and customer requirements. Our architecture provides a flexible means for service providers to optimize business performance. Based on the historical performance, extant context, and optimising business rules, the appropriate …

The Least-Squares Finite Element Method For Grid Deformation And Meshfree Applications, Dionisio Laeber Fleitas

Mathematics Dissertations

Grid adaptation is often needed to improve the numerical solution of a Partial Differential Equation (PDE), due to, for example, shock waves and boundary layers. In moving boundary problems, the grid needs to be regenerated or adapted to fit the new domain. In this work, a LSFEM deformation method is developed for grid generation on fixed or moving domains. The LSFEM is a finite-elements method which seeks to minimize the PDE residual equation through the least-squares method. A new class of numerical methods currently being researched is the meshfree methods, in which the main goal is to numerically solve PDEs …

Protection Against Experimental Autoimmune Myocarditis Is Mediated By Interleukin-10-Producing T Cells That Are Controlled By Dendritic Cells, Ya Li, Janet S. Heuser, Stanley D. Kosanke, Mark E. Hemric, Madeleine W. Cunningham

Faculty Publications and Presentations

Experimental autoimmune myocarditis (EAM) can be induced in the Lewis rat by cardiac myosin or its cryptic S2-16 peptide epitope (amino acids1052 to 1076). To investigate cellular mechanisms and the role of antigen-presenting cells in regulation of myocarditis, we induced protection against EAM in Lewis rats by administration of S2-16 peptide in incomplete Freund’s adjuvant (IFA). Protection to EAM was associated with activation of S2-16-reactive splenocytes secreting high levels of interleukin (IL)-10 and reduced levels of interferon- and IL-2. Adoptive transfer of S2-16:IFA-induced splenocytes producing IL-10 suppressed myocarditis induction in syngeneic recipients, suggesting their regulatory cell nature. However, exposure of …

The Crest, Summer 2005, Virginia Institute Of Marine Science

Reports

Table of Contents:

• Collaborative project gets to the bottom of oyster questions
• Rare crab may hold genetic secrets
• Shark trip brings research career full circle
• ICCAT adopts ban on "shark finning"
• Fisheries hires Fabrizio
• VIMS pair win Environmental Heroes Award
• Friedrichs and Steinberg receive faculty awards
• Trio tops citation analysis
• Fisheries partnership aids sturgeon restoration
• Researchers test beach-nourishment protocol
• CBNERR brings Bay education to local schools
• Hardaway selected to serve on national committee
• Emeritus Professor George Grant dies
• News Briefs

A Feature Specific Modular Approach For Pose And Illumination Invariant Face Recognition, Praveen Sankaran

Electrical & Computer Engineering Theses & Dissertations

A feature specific modular-PCA (Principal Component Analysis) approach on face images in multiple views for pose and illumination invariant face recognition is presented in this thesis. Principal components are extracted from different sub-modules of the image and are concatenated to make a single signature vector to represent a face region in a particular viewing angle. Additional principal components are extracted horn image regions representing key facial feature and are added as an extension of the signature vector. Feature specific modular-PCA approach is capable of recognizing faces in varying illumination conditions and facial expressions as the modular components represent the local …

Strategies For Analysis Of Unimodal And Multimodal Data For Simulation, Anshul Rai Sharma

Electrical & Computer Engineering Theses & Dissertations

The primary objective of this thesis is to provide strategies for analysis for data associated with simulation. Data analysis is an important part of the simulation process. Typically more stress is laid upon the development of the computer simulation while the data analysis takes a back seat. However, the accuracy of a simulation depends on the data driving it. In other words, any simulation is only as accurate as the input data fed into the simulation. Also, the output of simulation should be analyzed properly in order to validly estimate the performance of the system being simulated. The focus of …

Non-Linear And Linear Transformations Of Features For Robust Speech Recognition And Speaker Identification, Saurabh Prasad

Electrical & Computer Engineering Theses & Dissertations

Automatic speech recognizers perform poorly when training and test data are systematically different in terms of noise and channel characteristics. One manifestation of such differences is variations in the probability density functions (pdfs) between training and test features. Consequently, both automatic speech recognition and automatic speaker identification may be severely degraded. Previous attempts to mm1m1ze this problem include Cepstral Mean and Variance Normalization and transforming all speech features to a uni-variate Gaussian pdf. In this thesis, two techniques are presented for non-linearly scaling speech features to fit them to a target pdf - the first is based on the principles …

Descriptive Naming Of Context Data Providers, Norman H. Cohen, Paul Castro, Archan Misra

Research Collection School Of Computing and Information Systems

Much context data comes from mobile, transient, and unreliable sources. Such resources are best specified by descriptive names identifying what data is needed rather than which source is to provide it. The design of descriptive names has important consequences, but until now little attention has been focused on this problem. We propose a descriptive naming system for providers of context data that provides more flexibility and power than previous naming systems by classifying data providers into “provider kinds” that are organized in an evolving hierarchy of subkinds and superkinds. New provider kinds can be inserted in the hierarchy not only …

Strategic Assessment Of Information Security Maturity, Arcot Desai Narasimhalu, Dayasindhu Nagarajan, Raghavan Subramanian

Research Collection School Of Computing and Information Systems

CXOs are becoming increasingly interested in the information security maturity of their enterprises. This paper presents a CXO dashboard that will allow better management of the information security resources in an enterprise.

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …

An Informatization Of Society Approach To E-Government: Analyzing Singapore’S E-Government Efforts, Calvin M. L. Chan, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Despite the much publicized benefits of e-government, many countries are experiencing difficulty in yielding success in their e-government initiatives. Studies which adopt the national e-government initiatives as the unit of analysis remain largely rare. This paper aspires to provide an analysis of Singapore’s widely acclaimed success in the e-government effort at the national level to allow other countries to learn and gain from its experience. Using the ‘Conceptual Framework for the Informatization of Society’ in facilitating the data analysis, implications are drawn to offer insights for the considerations of e-government practitioners. Theoretical implications are also derived through positing that the …

Multibiometrics Based On Palmprint And Handgeometry, Xiao-Yong Wei, Dan Xu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper described our approach of multibiometrics in a single image. Firstly, a new method for capturing the key points of hand geometry is proposed. Then, we described our new method of palmprint feature extracting. By using projection transform and wavelet transform, this method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. We also proposed a twice segmentation method for handgeometry feature extraction. In the processing of feature matching, we analyzed the weakness of the traditional Euclidian Square Norm method, and introduced an improved method. The experimental results …

Energy Efficient Windows, Leona Hawks, Celia Peterson

All Current Publications

No abstract provided.

Synthesis Of Distributed Processes From Scenario-Based Specifications, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Given a set of sequence diagrams, the problem of synthesis is of deciding whether there exists a satisfying object system and if so, synthesize one automatically. It is crucial in the development of complex systems, since sequence diagrams serve as the manifestation of use cases and if synthesizable they could lead directly to implementation. It is even more interesting (and harder) if the synthesized object system is distributed. In this paper, we propose a systematic way of synthesizing distributed processes from Live Sequence Charts. The basic idea is to first construct a CSP specification from the LSC specification, and then …

Interannual Variation Of Stratification In Lower Chesapeake Bay, Christopher S. Katzenmiller

OES Theses and Dissertations

Stratification in the water column can prove to be an important indicator to the state of the water column and ecosystem. The focus of this research is to evaluate trends in stratification in the Lower Chesapeake Bay. Detailed analysis was performed on a 14 year data set to study interannual variation in the region of study. Potential energy anomaly was used to quantify stratification. Potential energy anomaly is the amount of energy required to mix a water column. It is determined from the vertical density structure of density. Potential energy anomaly is the departure of potential energy from climate conditions. …

Energy Efficient Appliances, Leona Hawks, Celia Peterson

All Current Publications

No abstract provided.

Checklist To Determine Energy Efficiency Of A Home, Leona Hawks

All Current Publications

No abstract provided.

Insulating Concrete Forms (Icfs), Leona Hawks, Koa Percer

All Current Publications

No abstract provided.

Lighting, Leona Hawks, Celia Peterson

All Current Publications

No abstract provided.