Computer Sciences Commons^™

Towards A Stronger Peer-To-Peer Anonymous System, Arjun R. Nambiar

Computer Science and Engineering Theses - Archive

Anonymous communications systems on the Internet provides protection against eavesdroppers and others that seek to link users with their communications. These systems have many important applications in areas such as law enforcement, intelligence gathering, business privacy, anonymous publishing, and personal privacy. Currently deployed systems rely on a relatively small set of advertised servers to forward messages for the user. These systems can suffer from scalability problems, with potentially large bandwidth and system overhead costs, and the servers themselves can be targets of direct attacks. Peer-to-peer anonymous communications systems, such as Tarzan[1] and MorphMix [2], have been proposed as a way …

Investigation Of Techniques To Increase The Scalability Of Graph-Based Data Mining Algorithms., Srilatha Inavolu

Computer Science and Engineering Theses - Archive

Frequent subgraph pattern recognition and graph-based relational learning have been an emerging area of data mining research with scientific and commercial applications. At the kernel of these algorithms are the computationally-expensive graph and subgraph isomorphism tests. The graph isomorphism problem consists in deciding whether two graphs are isomorphic i.e., whether there is a one-one mapping between the vertices of the two graphs that respects the edge connections. Many graphs will be depicted quite differently but in actuality have the same inherent structure. This leads to the isomorphism problem. The graph isomorphism problem belongs to the class of NP problems and …

Multiple Object Tracking Using Particle Filters, Hwangryol Ryu

Computer Science and Engineering Theses - Archive

We describe a novel extension to the Particle filter algorithm for tracking multiple objects. The recently proposed algorithms and the variants for multiple object tacking algorithms estimate multi-modal posterior distributions that potentially represent the multiple peaks (i.e., multiple tracked objects). However, the speci¯c state representation does not demonstrate birth, death and more importantly partial/complete occlusion of the objects. Furthermore, the weakness of the Particle Filter such that the representation may increasingly bias the posterior density estimates toward objects with dominant likelihood makes the multiple object tracking algorithms more di±cult. To circumvent a sample depletion problem and maintain the computational complexity …

Supervised Learning From Embedded Subgraphs, Joseph T. Potts

Computer Science and Engineering Dissertations - Archive

We develop a machine learning algorithm which learns rules for classification from training examples in a graph representation. However, unlike most other such algorithms which use one graph for each example, ours allows all of the training examples to be in a single, connected graph. We employ the Minimum Description Length principle to produce a novel performance metric for judging the value of a learned classification. We implement the algorithm by extending the Subdue graph-based learning system. Finally, we demonstrate the use of the new system in two different domains, earth science and homeland security.

Scalable Approaches For Supporting Mpi-Io Atomicity, Peter Aarestad, George K. Thiruvathukal, Avery Ching, Alok Choudhary

Computer Science: Faculty Publications and Other Works

Scalable atomic and parallel access to noncontiguous regions of a file is essential to exploit high performance I/O as required by large-scale applications. Parallel I/O frameworks such as MPI I/O conceptually allow I/O to be defined on regions of a file using derived datatypes. Access to regions of a file can be automatically computed on a perprocessor basis using the datatype, resulting in a list of (offset, length) pairs. We describe three approaches for implementing lock serving (whole file, region locking, and byterange locking) and compare the various approaches using three noncontiguous I/O benchmarks. We present the details of the …

Semantic Analytics Visualization, Leonidas Deligiannidis, Amit P. Sheth, Boanerges Aleman-Meza

Kno.e.sis Publications

In this paper we present a new tool for semantic analytics through 3D visualization called “Semantic Analytics Visualization” (SAV). It has the capability for visualizing ontologies and meta-data including annotated web-documents, images, and digital media such as audio and video clips in a synthetic three-dimensional semi-immersive environment. More importantly, SAV supports visual semantic analytics, whereby an analyst can interactively investigate complex relationships between heterogeneous information. The tool is built using Virtual Reality technology which makes SAV a highly interactive system. The backend of SAV consists of a Semantic Analytics system that supports query processing and semantic association discovery. Using a …

Multiorder Multidimensional Systems : Computation Of The Transfer Function Using The Dft, Marinos Theodorou Michael

Theses, Dissertations and Culminating Projects

In this thesis the discrete Fourier transform is used for determining the coefficients of the determinantal polynomial and the coefficients of the adjoint polynomial matrix for four systems/models. The main contribution of this thesis include:

• A method for computing the transfer function of a second-order 2D system using the DFT.

• A method for computing the transfer function of a generalized second-order 2D system using the DFT.

• The second-order 2D systems was extended to k-oider n-dimensions.

• The generalized second order 2D system was extended to generalized fc—order n— dimensions.

• A method for computing the transfer function …

A Survey Of The Methods To Find Probability Density Functions, Nancy Picinic Ricca

Theses, Dissertations and Culminating Projects

Various methods are described in this thesis that will approximate probability density functions (PDF), also known as invariant measures for chaotic maps. When studying discrete dynamical systems, the measure of a map is important in describing its behavior because it captures the statistics of long term simulations. Being invariant means that this distribution remains the same, no matter when you observe it. The main goal is to understand how to obtain these PDFs for various one-dimensional maps using alternative methods to time series data.

The methods studied in this thesis include the Z-matrix and the Frobenius-Perron Operator, which are analytic …

Mutual Knowledge And Its Impact On Virtual Team Performance, Alanah Davis, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper describes the notion of mutual knowledge and its potential impact on virtual team performance. Based on a review of the literature, including proponents and opponents for the concept of mutual knowledge in group interaction, we suggest that there is a gap in our understanding of what is known about mutual knowledge as it impacts team dynamics and ultimately virtual team performance. We conclude the paper by discussing the importance of mutual knowledge for virtual team performance and the research issues that need to be addressed in this domain.

Electronic Medical Records: Barriers To Adoption And Diffusion, Halbana Tarmizi, Deepak Khazanchi, Cherie Noteboom

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The primary goal of this paper is to explore why information technology (IT) solutions such as electronic medical records (EMR) have failed to gain a foothold in the healthcare sector. Based on a review of extant research, we propose a framework for classifying the barriers to the adoption and diffusion of EMR in the healthcare sector. We map all barriers reported in the literature onto the classification scheme to demonstrate its efficacy. We conclude by suggesting potential opportunities for applying the classification framework to research and practice.

Boundary Behavior Of Laplace Transforms, Timothy Ferguson

Honors Theses

In this thesis, we examine the boundary behavior of Laplace transforms (as analytic functions on the right and left half planes) of certain bounded functions. The types of bounded functions we consider are Fourier transforms of measures and almost periodic functions.

Risks Of Using Ap Locations Discovered Through War Driving, Minkyong Kim, Jeffrey J. Fielding, David Kotz

Dartmouth Scholarship

Many pervasive-computing applications depend on knowledge of user location. Because most current location-sensing techniques work only either indoors or outdoors, researchers have started using 802.11 beacon frames from access points (APs) to provide broader coverage. To use 802.11 beacons, they need to know AP locations. Because the actual locations are often unavailable, they use estimated locations from \em war driving. But these estimated locations may be different from actual locations. In this paper, we analyzed the errors in these estimates and the effect of these errors on other applications that depend on them. We found that the estimated AP locations …

Sound Source Localization And Separation, Biniyam Tesfaye Taddese

Mathematics, Statistics, and Computer Science Honors Projects

People face the problem of sound source localization and separation in situations where they attempt to localize and focus on a source of sound among a dissonance of conversations and background noise. This paper synthesizes a sound source localization routine. We utilize a general source separation technique, Independent Component Analysis.. Particularly, basic ICA was applied to separate mixtures of low frequency, narrow band, non-Gaussian signals by using closely spaced uni-directional microphones. The localization routine worked with an average condition number of 10. The routine was tested on data collected in a laboratory.

Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical need, while the uncertainty inherent to the mobile environment makes missing context values a major concern. This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive experiments on a restaurant recommender system showed that our mechanism can accurately discover causal dependencies among context, thereby enabling the effective identification of the minimal set of important context for a specific user and task, as well as providing highly accurate recommendations even …

Fuzzy State Aggregation And Off-Policy Reinforcement Learning For Stochastic Environments, Dean C. Wardell, Gilbert L. Peterson

Faculty Publications

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the environment it is operating in changes. This ability to learn in an unsupervised manner in a changing environment is applicable in complex domains through the use of function approximation of the domain’s policy. The function approximation presented here is that of fuzzy state aggregation. This article presents the use of fuzzy state aggregation with the current policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF), exceeding the learning rate …

Scalability In A Secure Distributed Proof System, Kazuhiro Minami, David Kotz

Dartmouth Scholarship

A logic-based language is often adopted in systems for pervasive computing, because it provides a convenient way to define rules that change the behavior of the systems dynamically. Those systems might define rules that refer to the users' context information to provide context-aware services. For example, a smart-home application could define rules referring to the location of a user to control the light of a house automatically. In general, the context information is maintained in different administrative domains, and it is, therefore, desirable to construct a proof in a distributed way while preserving each domain's confidentiality policies. In this paper, …

Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo

Research Collection School Of Computing and Information Systems

Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms have been proposed to obtain locally or globally optimal policies. Unfortunately, most of these algorithms have either been explicitly designed or experimentally evaluated assuming knowledge of a starting belief point, an assumption that often does not hold in complex, uncertain domains. Instead, in such domains, it is important for agents to explicitly plan over continuous belief spaces. This paper provides a novel algorithm to explicitly compute finite horizon policies over continuous belief spaces, without restricting the space of …

Time-Dependent Semantic Similarity Measure Of Queries Using Historical Click-Through Data, Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma

Research Collection School Of Computing and Information Systems

It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of click-through data logged by Web search engines, which record the interactions between users and the search engines. Most existing approaches employ the click-through data for similarity measure of queries with little consideration of the temporal factor, while the click-through data is often dynamic and contains rich temporal information. In this paper we present a new framework of time-dependent query semantic similarity model on exploiting the temporal characteristics of historical click-through data. The intuition is that more accurate semantic similarity values between …

Efficient Querying And Resource Management Using Distributed Presence Information In Converged Networks, Dipanjan Chakraborty, Koustuv Dasgupta, Archan Misra

Research Collection School Of Computing and Information Systems

Next-generation converged networks shall deliver many innovative services over the standardized SIPbased IMS signaling infrastructure. Several such services exploit the joint presence information of a consumer, i.e. SIP entity requesting a service, and a vendor, i.e. SIP resource providing a service. Presence information is a collection of contextual attributes (e.g. location, availability, reputation), some of which change dynamically. Moreover, this collective presence information is distributed across multiple presence servers. While performing query matching based on joint presence information, a server usually routes each query to a locally available resource. However, skews in the spatio-temporal distribution of queries and resources may …

Task Scheduling And Simulation, Martin Lee Mayne

Undergraduate Honors Capstone Projects

Scheduling is a problem that is not only common computer science, but which also comes up in a variety of real world situations. Whether multi-threading computer processes, scheduling airport traffic, optimizing assembly line production and manufacturing, or ensuring that enough employees are on the floor at a given time, scheduling is important for increasing efficiency, reducing costs, optimizing production, and meeting deadlines. Scheduling has been used throughout history and has increased in efficacy through the years. Modem computerized scheduling techniques are typically much better than human calculations and often produce surprising insights and results which would have been otherwise passed …

Large-Scale Text Categorization By Batch Mode Active Learning, Steven C. H. Hoi, Rong Jin, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the human efforts in labeling text documents for building reliable classification models. In the past, there have been many studies on applying active learning methods to automatic text categorization, which try to select the most informative documents for labeling manually. Most of these studies focused on selecting a single unlabeled document in each iteration. As a result, the text categorization model has to be retrained after each labeled document is solicited. In this paper, we present …

Real-Time Non-Rigid Shape Recovery Via Active Appearance Models For Augmented Reality, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One main challenge in Augmented Reality (AR) applications is to keep track of video objects with their movement, orientation, size, and position accurately. This poses a challenging task to recover nonrigid shape and global pose in real-time AR applications. This paper proposes a novel two-stage scheme for online non-rigid shape recovery toward AR applications using Active Appearance Models (AAMs). First, we construct 3D shape models from AAMs offline, which do not involve processing of the 3D scan data. Based on the computed 3D shape models, we propose an efficient online algorithm to estimate both 3D pose and non-rigid shape parameters …

Clip-Based Similarity Measure For Query-Dependent Clip Retrieval And Video Summarization, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to visual and granularity factors. We apply the similarity measure for two tasks: retrieval and summarization. In video retrieval, a hierarchical retrieval framework is constructed based on MM and OM. The validity of the framework is theoretically proved and empirically verified on a video database of 21 …

Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

Motivated by the studies in Gestalt principle, this paper describes a novel approach on the adaptive selection of visual features for trademark retrieval. We consider five kinds of visual saliencies: symmetry, continuity, proximity, parallelism and closure property. The first saliency is based on Zernike moments, while the others are modeled by geometric elements extracted illusively as a whole from a trademark. Given a query trademark, we adaptively determine the features appropriate for retrieval by investigating its visual saliencies. We show that in most cases, either geometric or symmetric features can give us good enough accuracy. To measure the similarity of …

Mining Rdf Metadata For Generalized Association Rules: Knowledge Discovery In The Semantic Web Era, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of emphgeneralization closure for systematic over-generalization reduction.

On In-Network Synopsis Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang

Research Collection School Of Computing and Information Systems

The emergence of sensor networks enables applications that deploy sensors to collaboratively monitor environment and process data collected. In some scenarios, we are interested in using join queries to correlate data stored in different regions of a sensor network, where the data volume is large, making it prohibitive to transmit all data to a central server for joining. In this paper, we present an in-network synopsis join strategy for evaluating join queries in sensor networks with communication efficiency. In this strategy, we prune data that do not contribute to the join results in the early stage of the join processing, …

Osprey: A Practical Type System For Validating Dimensional Unit Correctness Of C Programs, Lingxiao Jiang, Zhendong Su

Research Collection School Of Computing and Information Systems

Misuse of measurement units is a common source of errors in scientific applications, but standard type systems do not prevent such errors. Dimensional analysis in physics can be used to manually detect such errors in physical equations. It is, however, not feasible to perform such manual analysis for programs computing physical equations because of code complexity. In this paper, we present a type system to automatically detect potential errors involving measurement units. It is constraint-based: we model units as types and flow of units as constraints. However, standard type checking algorithms are not powerful enough to handle units because of …

Multiple Masks-Based Pixel Comparison Steganalysis Method For Mobile Imaging, Sos S. Agaian, Gilbert L. Peterson, Benjamin M. Rodriguez

Faculty Publications

No abstract provided.

Design And Implementation Of A Web-Based Lead Management System Using Oracle And Coldfusion Technologies, James Darschewski

Regis University Student Publications (comprehensive collection)

In business a key to being successful is being able to identify who your customers are and evaluating their needs. Most businesses are not only comprised of a single customer; therefore, there is a need to retain customer information and to track the customer from initial contact to the point of sale. While there are numerous off the shelf products that can store customer data, often times they do not easily allow for modifications and many of these products would require some sort of wide area network (WAN), which could incur extensive costs, in order for highly distributed sales people …

Controlling Factors In Evaluating Path-Sensitive Error Detection Techniques, Matthew B. Dwyer, Suzette Person, Sebastian Elbaum

School of Computing: Technical Reports

Recent advances in static program analysis have made it possible to detect errors in applications that have been thoroughly tested and are in wide-spread use. The ability to find errors that have eluded traditional validation methods is due to the development and combination of sophisticated algorithmic techniques that are embedded in the implementations of analysis tools. Evaluating new analysis techniques is typically performed by running an analysis tool on a collection of subject programs, perhaps enabling and disabling a given technique in different runs. While seemingly sensible, this approach runs the risk of attributing improvements in the cost-effectiveness of the …