Digital Commons Network^™

Cosign: A Parallel Algorithm For Coordinated Traffic Signal Control, Shih-Fen Cheng, Marina A. Epelman, Robert L. Smith

Research Collection School Of Computing and Information Systems

The problem of finding optimal coordinated signal timing plans for a large number of traffic signals is a challenging problem because of the exponential growth in the number of joint timing plans that need to be explored as the network size grows. In this paper, the game-theoretic paradigm of fictitious play to iteratively search for a coordinated signal timing plan is employed, which improves a system-wide performance criterion for a traffic network. The algorithm is robustly scalable to realistic-size networks modeled with high-fidelity simulations. Results of a case study for the city of Troy, MI, where there are 75 signalized …

Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang

Computer Science Faculty Publications

Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …

Audio Similarity Measure By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo, Cuihua Fang, Xiaoou Chen, Jianguo Xiao

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for the similarity measure and ranking of audio clips by graph modeling and matching. Instead of using frame-based or salient-based features to measure the acoustical similarity of audio clips, segment-based similarity is proposed. The novelty of our approach lies in two aspects: segment-based representation, and the similarity measure and ranking based on four kinds of similarity factors. In segmentbased representation, segments not only capture the change property of audio clip, but also keep and present the change relation and temporal order of audio features. In the similarity measure and ranking, four kinds of similarity …

Fast Tracking Of Near-Duplicate Keyframes In Broadcast Domain With Transitivity Propagation, Chong-Wah Ngo, Wan-Lei Zhao, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

The identification of near-duplicate keyframe (NDK) pairs is a useful task for a variety of applications such as news story threading and content-based video search. In this paper, we propose a novel approach for the discovery and tracking of NDK pairs and threads in the broadcast domain. The detection of NDKs in a large data set is a challenging task due to the fact that when the data set increases linearly, the computational cost increases in a quadratic speed, and so does the number of false alarms. This paper explores the symmetric and transitive nature of near-duplicate for the effective …

New Tracking Filter Algorithm Using Input Parameter Estimation, Corey M. Broussard

Theses and Dissertations

A new method for the design of tracking filters for maneuvering targets, based on kinematic models and input signals estimation, is developed. The input signal's level, u is considered a continuous variable and consequently the input estimation problem is posed as a purely parameter estimation problem. Moreover, the application of the new tracking filter algorithm is not contingent on distinguishing maneuvering and non-maneuvering targets, and does not require the detection of maneuver onset. The filter will automatically detect the onset of a maneuver. Furthermore, an estimate of the target's acceleration is also obtained with reasonable precision. This opens the door …

Optimizing The Replication Of Multi-Quality Web Applications Using Aco And Wolf, Judson C. Dressler

Theses and Dissertations

This thesis presents the adaptation of Ant Colony Optimization to a new NP-hard problem involving the replication of multi-quality database-driven web applications (DAs) by a large application service provider (ASP). The ASP must assign DA replicas to its network of heterogeneous servers so that user demand is satisfied and replica update loads are minimized. The algorithm proposed, AntDA, for solving this problem is novel in several respects: ants traverse a bipartite graph in both directions as they construct solutions, pheromone is used for traversing from one side of the bipartite graph to the other and back again, heuristic edge values …

Wireless Indoor Positioning System With Enhanced Nearest Neighbors In Signal Space Algorithm, Quang Tran, Juki Wirawan Tantra, Ah-Hwee Tan, Ah-Hwee Tan, Kin-Choong Yow, Dongyu Qiu

Research Collection School Of Computing and Information Systems

With the rapid development and wide deployment of wireless Local Area Networks (WLANs), WLAN-based positioning system employing signal-strength-based technique has become an attractive solution for location estimation in indoor environment. In recent years, a number of such systems has been presented, and most of the systems use the common Nearest Neighbor in Signal Space (NNSS) algorithm. In this paper, we propose an enhancement to the NNSS algorithm. We analyze the enhancement to show its effectiveness. The performance of the enhanced NNSS algorithm is evaluated with different values of the parameters. Based on the performance evaluation and analysis, we recommend some …

Mining Rdf Metadata For Generalized Association Rules, 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 generalization closure for systematic over-generalization reduction. Empirical experiments conducted on real world RDF data sets show that our method can substantially reduce pattern redundancy and perform much better than the original generalized association rule mining algorithm Cumulate in term of time efficiency.

Learning The Unified Kernel Machines For Classification, Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang

Research Collection School Of Computing and Information Systems

Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel Machines (UKM) from both labeled and unlabeled data. Our proposed framework integrates supervised learning, semi-supervised kernel learning, and active learning in a unified solution. In the suggested framework, we particularly focus our attention on designing a new semi-supervised kernel learning method, i.e., Spectral Kernel Learning (SKL), which is built on the principles of kernel target alignment and unsupervised kernel design. Our algorithm is related to an equivalent quadratic programming problem that can be efficiently …

An Adaptive Algorithm To Identify Ambiguous Prostate Capsule Boundary Lines For Three-Dimensional Reconstruction And Quantitation, Rania Yousry Hussein

Electrical & Computer Engineering Theses & Dissertations

Currently there are few parameters that are used to compare the efficiency of different methods of cancerous prostate surgical removal. An accurate assessment of the percentage and depth of extra-capsular soft tissue removed with the prostate by the various surgical techniques can help surgeons determine the appropriateness of surgical approaches. Additionally, an objective assessment can allow a particular surgeon to compare individual performance against a standard. In order to facilitate 3D reconstruction and objective analysis and thus provide more accurate quantitation results when analyzing specimens, it is essential to automatically identify the capsule line that separates the prostate gland tissue …

Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience.

Interacting With Web Hierarchies, Saverio Perugini, Naren Ramakrishnan

Computer Science Faculty Publications

Web site interfaces are a particularly good fit for hierarchies in the broadest sense of that idea, i.e. a classification with multiple attributes, not necessarily a tree structure. Several adaptive interface designs are emerging that support flexible navigation orders, exposing and exploring dependencies, and procedural information-seeking tasks. This paper provides a context and vocabulary for thinking about hierarchical Web sites and their design. The paper identifies three features that interface to information hierarchies. These are flexible navigation orders, the ability to expose and explore dependencies, and support for procedural tasks. A few examples of these features are also provided

Strategies For Encoding Xml Documents In Relational Databases: Comparisons And Contrasts., Jonathan Lee Leonard

Electronic Theses and Dissertations

The rise of XML as a de facto standard for document and data exchange has created a need to store and query XML documents in relational databases, today's de facto standard for data storage. Two common strategies for storing XML documents in relational databases, a process known as document shredding, are Interval encoding and ORDPATH Encoding. Interval encoding, which uses a fixed mapping for shredding XML documents, tends to favor selection queries, at a potential cost of O(N) for supporting insertion queries. ORDPATH Encoding, which uses a looser mapping for shredding XML, supports fixed-cost insertions, at a potential cost of …

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.

A Unified Log-Based Relevance Feedback Scheme For Image Retrieval, Steven Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has emerged as a powerful tool to boost the retrieval performance in content-based image retrieval (CBIR). In the past, most research efforts in this field have focused on designing effective algorithms for traditional relevance feedback. Given that a CBIR system can collect and store users' relevance feedback information in a history log, an image retrieval system should be able to take advantage of the log data of users' feedback to enhance its retrieval performance. In this paper, we propose a unified framework for log-based relevance feedback that integrates the log of feedback data into the traditional relevance feedback …

Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville

Theses and Dissertations

An algorithm is presented to simulate fluid dynamics on a three qubit type II quantum computer: a lattice of small quantum computers that communicate classical information. The algorithm presented is called a three qubit factorized quantum lattice gas algorithm. It is modeled after classical lattice gas algorithms which move virtual particles along an imaginary lattice and change the particles’ momentums using collision rules when they meet at a lattice node. Instead of moving particles, the quantum algorithm presented here moves probabilities, which interact via a unitary collision operator. Probabilities are determined using ensemble measurement and are moved with classical communications …

Multiframe Shift Estimation, Stephen A. Bruckart

Theses and Dissertations

The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …

An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris

Theses and Dissertations

The purpose of this research is to develop an algorithm to detect obscured images in 3-D LADAR data. The real data used for this research was gathered using a FLASH LADAR system under development at AFRL/SNJM. The system transmits light with a wavelength of 1.55 micrometers and produces 20 128 X 128 temporally resolved images from the return pulse separated by less than 2 nanoseconds in time. New algorithms for estimating the range to a target in 3-D FLASH LADAR data were developed. Results from processing real data are presented and compared to the traditional correlation receiver for extracting ranges …

Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson

Theses and Dissertations

Decision level fusion (DLF) algorithms combine outputs of multiple single sensors to make one confident declaration of a target. This research compares performance results of a DLF algorithm using measured data and a proven ATR system with results from simulated data and a modeled ATR system. This comparison indicates that DLF offers significant performance improvements over single sensor looks. However, results based on simulated data and a modeled ATR are slightly optimistic and overestimate results from measured data and a proven ATR system by nearly 10% over all targets tested.

A Hybrid Scatter Search/Electromagnetism Meta-Heuristic For Project Scheduling, Dieter Debels, Bert De Reyck, Roel Leus, Mario Vanhoucke

Research Collection Lee Kong Chian School Of Business

In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions for relatively large instances. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and from a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory. We present computational …

The Pseudosquares Prime Sieve, Jonathan P. Sorenson

Scholarship and Professional Work - LAS

We present the pseudosquares prime sieve, which finds all primes up to n.

Fast Bounds On The Distribution Of Smooth Numbers, Scott T. Parsell, Jonathan P. Sorenson

Scholarship and Professional Work - LAS

In this paper we present improvements to Bernstein’s algorithm, which finds rigorous upper and lower bounds for (x, y).

Place-Valued Logics Around Cybernetic Ontology, The Bcl And Afosr, Rudolf Kaehr

Rudolf Kaehr

No abstract provided.

From Ruby To Rudy, Rudolf Kaehr

Rudolf Kaehr

No abstract provided.

The Chinese Challenge. Hallucinations For Other Futures, Rudolf Kaehr

Rudolf Kaehr

The main question is: What can we learn from China that China is not teaching us? It is proposed that a study of polycontextural logic and morphogrammatics could be helpful to discover this new kind of rationality.

Efficient Scheduling For Sdmg Cioq Switches, Mei Yang, S. Q. Zheng

Electrical & Computer Engineering Faculty Research

Combined input and output queuing (CIOQ) switches are being considered as high-performance switch architectures due to their ability to achieve 100% throughput and perfectly emulate output queuing (OQ) switch performance with a small speedup factor S. To realize a speedup factor S, a conventional CIOQ switch requires the switching fabric and memories to operate S times faster than the line rate. In this paper, we propose to use a CIOQ switch with space-division multiplexing expansion and grouped input/output ports (SDMG CIOQ switch for short) to realize speedup while only requiring the switching fabric and memories to operate at the line …

Realtime Query Expansion And Procedural Interfaces For Information Hierarchies, Saverio Perugini

Computer Science Faculty Publications

We demonstrate the use of two user interfaces for interacting with web hierarchies. One uses the dependencies underlying a hierarchy to perform real-time query expansion and, in this way, acts as an in situ feedback mechanism. The other enables the user to cascade the output from one interaction to the input of another, and so on, and, in this way, supports procedural information-seeking tasks without disrupting the flow of interaction.

Information Assurance Through Binary Vulnerability Auditing, William B. Kimball, Saverio Perugini

Computer Science Faculty Publications

The goal of this research is to develop improved methods of discovering vulnerabilities in software. A large volume of software, from the most frequently used programs on a desktop computer, such as web browsers, e-mail programs, and word processing applications, to mission-critical services for the space shuttle, is unintentionally vulnerable to attacks and thus insecure. By seeking to improve the identification of vulnerabilities in software, the security community can save the time and money necessary to restore compromised computer systems. In addition, this research is imperative to activities of national security such as counterterrorism. The current approach involves a systematic …

Classical And Quantum Algorithms For Finding Cycles, Jill Cirasella

Publications and Research

Quantum computing—so weird, so wonderful—inspires much speculation about the line between the possible and the impossible. (Of course, there is still unclarity about how “impossible” intractable problems are and about how “possible” quantum computers are.) This thesis takes a slightly different tack: instead of focusing on how to make the impossible possible, it focuses on how to make the possible easier.

More specifically, this paper discusses quantum algorithms for finding cycles in graphs, a problem for which polynomial-time classical algorithms already exist. It explains and compares the classical and quantum algorithms, and it introduces a few new algorithms and observations. …