Enhancement Technique For Aerial Images,
2011
Old Dominion University
Enhancement Technique For Aerial Images, Sertan Erkanli, Ahmet Gungor Pakfiliz, Jiang Li
Electrical & Computer Engineering Faculty Publications
Recently, we proposed an enhancement technique for uniformly and non-uniformly illuminated dark images that provides high color accuracy and better balance between the luminance and the contrast in images to improve the visual representations of digital images. In this paper we define an improved version of the proposed algorithm to enhance aerial images in order to reduce the gap between direct observation of a scene and its recorded image.
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning,
2011
Michigan State University
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning, Lei Wu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The authors present an online semantics preserving, metric learning technique for improving the bag-of-words model and addressing the semantic-gap issue. This article investigates the challenge of reducing the semantic gap for building BoW models for image representation; propose a novel OSPML algorithm for enhancing BoW by minimizing the semantic loss, which is efficient and scalable for enhancing BoW models for large-scale applications; apply the proposed technique for large-scale image annotation and object recognition; and compare it to the state of the art.
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach,
2011
Singapore Management University
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Research Collection School Of Computing and Information Systems
Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …
Random Automata Networks: Why Playing Dice Is Not A Vice,
2010
Portland State University
Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher
Systems Science Friday Noon Seminar Series
Random automata networks consist of a set of simple compute nodes interacting with each other. In this generic model, one or multiple model parameters, such as the the node interactions and/or the compute functions, are chosen at random. Random Boolean Networks (RBNs) are a particular case of discrete dynamical automata networks where both time and states are discrete. While traditional RBNs are generally credited to Stuart Kauffman (1969), who introduced them as simplified models of gene regulation, Alan Turing proposed unorganized machines as early as 1948. In this talk I will start with Alan Turing's early work on unorganized machines, …
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment,
2010
Singapore Management University
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Search engines are used to return a long list of hundreds or even thousands of videos in response to a query topic. Efficient navigation of videos becomes difficult and users often need to painstakingly explore the search list for a gist of the search result. This paper addresses the challenge of topical summarization by providing a timeline-based visualization of videos through matching of heterogeneous sources. To overcome the so called sparse-text problem of web videos, auxiliary information from Google context is exploited. Google Trends is used to predict the milestone events of a topic. Meanwhile, the typical scenes of web …
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects,
2010
Singapore Management University
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects, Rui Zhang, H.V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao
Research Collection School Of Computing and Information Systems
There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to …
Program Transformations For Information Personalization,
2010
University of Dayton
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Computer Science Faculty Publications
Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical …
Economic Optimization Of Offshore Wind Farms Using The Geometric Algorithm,
2010
Old Dominion University
Economic Optimization Of Offshore Wind Farms Using The Geometric Algorithm, Mahidhar Nandigam
Electrical & Computer Engineering Theses & Dissertations
The research project related to this thesis focuses on the optimization of electrical systems for offshore wind farms for a given capacity. The optimal design and planning is a critical issue for developing cost effectively Offshore Wind Farms in energy systems. The Geometric Optimization Algorithms approach has been adopted to develop an optimization program, where the main components of the electrical system of an offshore wind farm and key technical specifications are used as parameters to be optimized for a minimum cost with necessary constraints. The effectiveness of the optimization program can be evaluated with real-time comparison between offshore wind …
Electroencephalogram Artifact Removal Using A Wavelet Neural Network,
2010
Old Dominion University
Electroencephalogram Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen
Electrical & Computer Engineering Theses & Dissertations
A wavelet neural network (WNN) technique rs developed for electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural networks and the time/frequency property of wavelet, where the neural network was trained on a simulated dataset with known ground truths. The contribution of this thesis is two-fold. First, many EEG artifact removal algorithms, including regression based methods, require reference EOG signals, which are not always available. To remove EEG ai1ifacts, a WNN tries to learn the characteristics of the artifacts first and does not need reference EOG signals once trained. Second, WNNs are …
A Hoare Calculus For Graph Programs,
2010
Singapore Management University
A Hoare Calculus For Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
We present Hoare-style axiom schemata and inference rules for verifying the partial correctness of programs in the graph programming language GP. The pre- and postconditions of this calculus are the nested conditions of Habel, Pennemann and Rensink, extended with expressions for labels in order to deal with GP’s conditional rule schemata and infinite label alphabet. We show that the proof rules are sound with respect to GP’s operational semantics.
Detours Admitting Short Paths,
2010
University of Nevada, Las Vegas
Detours Admitting Short Paths, Reshma Koganti
UNLV Theses, Dissertations, Professional Papers, and Capstones
Finding shortest paths between two vertices in a weighted graph is a well explored problem and several efficient algorithms for solving it have been reported. We propose a new variation of this problem which we call the Detour Admitting Shortest Path Problem (DASPP).We present an efficient algorithm for solving DASPP. This is the first algorithm that constructs a shortest path such that each edge of the shortest path admits a detour with no more than k−hops. This algorithm has important applications in transportation networks. We also present implementation issues for the detour admitting shortest path algorithm.
Hoare Logic For Graph Programs,
2010
Singapore Management University
Hoare Logic For Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
We present a new approach for verifying programs written in GP (for Graph Programs), an experimental programming language for performing computations on graphs at a high level of abstraction. Taking a labelled graph as input, a graph program nondeterministically applies to it a number of graph transformation rules, directed by simple control constructs such as sequential composition and as-long-as-possible iteration. We adapt classical Hoare logic to the domain of graphs, and describe a system of sound proof rules for showing the partial correctness of graph programs.
Cloud Storage And Online Bin Packing,
2010
University of Nevada, Las Vegas
Cloud Storage And Online Bin Packing, Swathi Venigella
UNLV Theses, Dissertations, Professional Papers, and Capstones
Cloud storage is the service provided by some corporations (such as Mozy and Carbonite) to store and backup computer files. We study the problem of allocating memory of servers in a data center based on online requests for storage. Over-the-net data backup has become increasingly easy and cheap due to cloud storage. Given an online sequence of storage requests and a cost associated with serving the request by allocating space on a certain server one seeks to select the minimum number of servers as to minimize total cost. We use two different algorithms and propose a third algorithm; we show …
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering,
2010
Singapore Management University
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Learning a good distance metric plays a vital role in many multimedia retrieval and data mining tasks. For example, a typical content-based image retrieval (CBIR) system often relies on an effective distance metric to measure similarity between any two images. Conventional CBIR systems simply adopting Euclidean distance metric often fail to return satisfactory results mainly due to the well-known semantic gap challenge. In this article, we present a novel framework of Semi-Supervised Distance Metric Learning for learning effective distance metrics by exploring the historical relevance feedback log data of a CBIR system and utilizing unlabeled data when log data are …
On Decision Support For Deliberating With Constraints In Constrained Optimization Models,
2010
Singapore Management University
On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood
Research Collection School Of Computing and Information Systems
This paper introduces the Deliberation Decision Support System (DDSS). The DDSS obtains heuristically (using a genetic algorithm) solutions of interest for constrained optimization models. This is illustrated, without loss of generality, by generalized assignment problems. The DDSS also provides users with graphical tools that support post-solution deliberation for constrained optimization models. The DDSS and this paper, as befits practical concerns, are focused on deliberation with respect to the constraints of the models being used.
Merging Schemas In A Collaborative Faceted Classification System,
2010
Old Dominion University
Merging Schemas In A Collaborative Faceted Classification System, Jianxiang Li
Computer Science Theses & Dissertations
We have developed a system that improves access to a large, growing image collection by allowing users to collaboratively build a global faceted (multi-perspective) classification schema. We are extending our system to support both global and local schemas, where global schema provides a complete and uniform view of the collection whereas local schema provides a personal, possibly incomplete and idiosyncratic view of the collection. We argue that although users usually focus on their personal schemas, it is still desirable to have a global schema for the entire collection even if such local schemas are available. In order to keep the …
A Differential Absorption Model For Remote Sensing Of Atmospheric Pressure,
2010
Old Dominion University
A Differential Absorption Model For Remote Sensing Of Atmospheric Pressure, Shivam J. Shah
Electrical & Computer Engineering Theses & Dissertations
The goal of the project is to develop and test a "model based" radar processing strategy that is compatible with the concept of a "cognitive radar". The basic approach will be to develop a cognitive radar algorithm (genetic algorithm) based on the capabilities of an existing commercially available Software Radio. While the focus of this effort is the development of a candidate approach for genetic algorithm, the longer term goal would be to implement the approach using this software radio technology to provide a low cost radar processor. The proposed technology would use differential absorption radar working at the 50-56 …
Action Recognition Based On Multi-Level Representation Of 3d Shape,
2010
Old Dominion University
Action Recognition Based On Multi-Level Representation Of 3d Shape, Binu M. Nair
Electrical & Computer Engineering Theses & Dissertations
A novel algorithm is proposed in this thesis for recognizing human actions using a combination of two shape descriptors, one of which is a 3D Euclidean distance transform and the other based on the Radon transform. This combination captures the necessary variations from the space time shape for recognizing actions. The space time shapes are created by the concatenation of human body silhouettes across time. The comparisons are done against some common shape descriptors such as the zernike moments and Radon transform. This is also compared with an algorithm which uses the same concept of a space time shape and …
A First Practical Algorithm For High Levels Of Relational Consistency,
2010
University of Nebraska-Lincoln
A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reesons, Berthe Y. Choueiry, Christian Bessiere
School of Computing: Conference and Workshop Papers
Consistency properties and algorithms for achieving them are at the heart of the success of Constraint Programming. In this paper, we study the relational consistency property R(∗,m)C, which is equivalent to m-wise consistency proposed in relational databases. We also define wR(∗,m)C, a weaker variant of this property. We propose an algorithm for enforcing these properties on a Constraint Satisfaction Problem by tightening the existing relations and without introducing new ones. We empirically show that wR(∗,m)C solves in a backtrack-free manner all the instances of some CSP benchmark classes, thus hinting at the tractability of those classes.
An Application Of Automated Theorem Provers To Computer System Security: The Schematic Protection Model,
2010
Air Force Institute of Technology
An Application Of Automated Theorem Provers To Computer System Security: The Schematic Protection Model, Mitchell D.I. Hirschfeld
Theses and Dissertations
The Schematic Protection Model is specified in SAL and theorems about Take-Grant and New Technology File System schemes are proven. Arbitrary systems can be specified in SPM and analyzed. This is the first known automated analysis of SPM specifications in a theorem prover. The SPM specification was created in such a way that new specifications share the underlying framework and are configurable within the specifications file alone. This allows new specifications to be created with ease as demonstrated by the four unique models included within this document. This also allows future users to more easily specify models without recreating the …
