Theory and Algorithms Commons^™

Global Immutable Region Computation, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

A top-k query shortlists the k records in a dataset that best match the user's preferences. To indicate her preferences, the user typically determines a numeric weight for each data dimension (i.e., attribute). We refer to these weights collectively as the query vector. Based on this vector, each data record is implicitly mapped to a score value (via a weighted sum function). The records with the k largest scores are reported as the result. In this paper we propose an auxiliary feature to standard top-k query processing. Specifically, we compute the maximal locus within which the query vector incurs no …

Placing Videos On A Semantic Hierarchy For Search Result Navigation, Song Tan, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Organizing video search results in a list view is widely adopted by current commercial search engines, which cannot support efficient browsing for complex search topics that have multiple semantic facets. In this article, we propose to organize video search results in a highly structured way. Specifically, videos are placed on a semantic hierarchy that accurately organizes various facets of a given search topic. To pick the most suitable videos for each node of the hierarchy, we define and utilize three important criteria: relevance, uniqueness, and diversity. Extensive evaluations on a large YouTube video dataset demonstrate the effectiveness of our approach.

Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart

School of Computing: Dissertations, Theses, and Student Research

Geospatial information fusion is the process of synthesizing information from complementary data sources located at different points in space and time. Spatial phenomena are often measured at discrete locations by sensor networks, technicians, and volunteers; yet decisions often require information about locations where direct measurements do not exist. Traditional methods assume the spatial phenomena to be either discrete or continuous, an assumption that underlies and informs all subsequent analysis. Yet certain phenomena defy this dichotomy, alternating as they move across spatial and temporal scales. Precipitation, for example, appears continuous at large scales, but it can be temporally decomposed into discrete …

A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo

Research Collection School Of Computing and Information Systems

In this article, we propose a novel Hamming embedding kernel with informative bag-of-visual words to address two main problems existing in traditional BoW approaches for video semantic indexing. First, Hamming embedding is employed to alleviate the information loss caused by SIFT quantization. The Hamming distances between keypoints in the same cell are calculated and integrated into the SVM kernel to better discriminate different image samples. Second, to highlight the concept-specific visual information, we propose to weight the visual words according to their informativeness for detecting specific concepts. We show that our proposed kernels can significantly improve the performance of concept …

L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan

Research Collection School Of Computing and Information Systems

The wealth of information contained in online social networks has created a demand for the publication of such data as graphs. Yet, publication, even after identities have been removed, poses a privacy threat. Past research has suggested ways to publish graph data in a way that prevents the re-identification of nodes. However, even when identities are effectively hidden, an adversary may still be able to infer linkage between individuals with sufficiently high confidence. In this paper, we focus on the privacy threat arising from such link disclosure. We suggest L-opacity, a sufficiently strong privacy model that aims to control an …

Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm …

Colormoo: An Algorithmic Approach To Generating Color Palettes, Joshua Rael

CMC Senior Theses

Selecting one color can be done with relative ease, but this task becomes more difficult with each subsequent color. Colormoo is an online tool aimed at solving this problem. We implement three algorithms for generating color palettes based off of a starting color. Data is collected for each palette that is generated. Our analysis reveals two of the algorithms are preferred, but under different circumstances. Furthermore, we find that users prefer palettes containing colors that are compatible, but not too similar. With refined heuristics, we believe these techniques can be extended and applied beyond the field of graphic design alone.

Computing The Grounded Semantics In All The Subgraphs Of An Argumentation Framework: An Empirical Evaluation, Pierpaolo Dondio

Articles

Given an argumentation framework – with a finite set of arguments and the attack relation identifying the graph – we study how the grounded labelling of a generic argument a varies in all the subgraphs of . Since this is an intractable problem of above-polynomial complexity, we present two non-naïve algorithms to find the set of all the subgraphs where the grounded semantic assigns to argument a specific label . We report the results of a series of empirical tests over graphs of increasing complexity. The value of researching the above problem is two-fold. First, knowing how an argument behaves …

Fusion Of Visual And Thermal Images Using Genetic Algorithms, Sertan Erkanli, Jiang Li, Ender Oguslu, Shangce Gao (Ed.)

Electrical & Computer Engineering Faculty Publications

No abstract provided.

Toward Automatic Subpixel Registration Of Unmanned Airborne Vehicle Images, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Many applications require to register images within subpixel accuracy like computer vision especially super-resolution (SR) where the estimated subpixel shifts are very crucial in the reconstruction and restoration of SR images. In our work we have an optical sensor that is mounted on an unmanned airborne vehicle (UAV) and captures a set of images that contain sufficient overlapped area required to reconstruct a SR image. Due to the wind, The UAV may encounter rotational effects such as yaw, pitch and roll which can distort the acquired as well as processed images with shear, tilt or perspective distortions. In this paper …

Image Processing – I: Automated System For Fingerprint Image Enhancement Using Improved Segmentation And Gabor Wavelets, Amna Saeed, Anam Tariq, Usman Jawaid

International Conference on Information and Communication Technologies

This research revolves around the fingerprint image enhancement. It is used for automated fingerprint identification systems (AFIS) for extracting the best quality fingerprint images. Accurate feature extraction and identification is the basic theme of this enhancement. This paper is on the fingerprint image enhancement using wavelets. Wavelets are famous for their special localization property and orientation flow estimation. The proposed technique is basically comprises of three main steps: segmentation followed by image sharpening and then Gabor wavelet filtering. Segmentation distinguishes between image background and foreground which in turn reduces processing time. Our sharpening stage of enhancement algorithm sharpens the edges …

Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato

Research Collection School Of Computing and Information Systems

In today's world, organizations are faced with increasingly large and complex problems that require decision-making under uncertainty. Current methods for optimizing such decisions fall short of handling the problem scale and time constraints. We argue that this is due to existing methods not exploiting the inherent structure of the organizations which solve these problems. We propose a new model called the OrgPOMDP (Organizational POMDP), which is based on the partially observable Markov decision process (POMDP). This new model combines two powerful representations for modeling large scale problems: hierarchical modeling and factored representations. In this paper we make three key contributions: …

In-Degree Dynamics Of Large-Scale P2p Systems, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov

Computer Science Faculty Publications

This paper builds a complete modeling framework for understanding user churn and in-degree dynamics in unstructured P2P systems in which each user can be viewed as a stationary alternating renewal process. While the classical Poisson result on the superposition of n stationary renewal processes for n→∞ requires that each point process become sparser as n increases, it is often difficult to rigorously show this condition in practice. In this paper, we first prove that despite user heterogeneity and non-Poisson arrival dynamics, a superposition of edge-arrival processes to a live user under uniform selection converges to a Poisson process when …

Automatic Detection Of Aircraft Emergency Landing Sites, Yu-Fei Shen, Zia-Ur Rahman, Dean Krusienski, Jiang Li, Zia-Ur Rahman (Ed.), Stephen E. Reichenbach (Ed.), Mark Allen Neifeld (Ed.)

Electrical & Computer Engineering Faculty Publications

An automatic landing site detection algorithm is proposed for aircraft emergency landing. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the external environmental factors that can impair …

Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)

Electrical & Computer Engineering Faculty Publications

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, …

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.

A Randomized Sublinear Time Parallel Gcd Algorithm For The Erew Pram, Jonathan P. Sorenson

Scholarship and Professional Work - LAS

We present a randomized parallel algorithm that computes the greatest common divisor of two integers of n bits in length with probability 1−o(1) that takes O(n log logn/ logn) time using O(n6 + ) processors for any > 0 on the EREW PRAM parallel model of computation. The algorithm either gives a correct answer or reports failure. We believe this to be the first randomized sublinear time algorithm on the EREW PRAM for this problem.

Nearest Neighbor Search With Strong Location Privacy, Stavros Papadopoulos, Spiridon Bakiras, Dimitris Papadias

Publications and Research

The tremendous growth of the Internet has significantly reduced the cost of obtaining and sharing information about individuals, raising many concerns about user privacy. Spatial queries pose an additional threat to privacy because the location of a query may be sufficient to reveal sensitive information about the querier. In this paper we focus on k nearest neighbor (kNN) queries and define the notion of strong location privacy, which renders a query indistinguishable from any location in the data space. We argue that previous work fails to support this property for arbitrary kNN search. Towards this end, we introduce methods that …

Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan

Theses and Dissertations

Range estimation algorithms have been applied to Laser Detection and Ranging (LADAR) data to test for accuracy and precision. Data was acquired from Matlab® simulations and an experiment using the Advanced Scientific Concepts 3-D flash LADAR camera. Simulated LADAR data was based on a Gaussian pulse shape model with Poisson noise added. Simulations were performed to test range estimation algorithm performance with respect to waveform position within the range gate. The effectiveness of each algorithm is presented in terms of its average root mean square error and standard deviation in 1000 trials. The measured data experiment examined the effectiveness of …

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …

Finding Irc-Like Meshes Sans Layer 7 Payloads, Akshay Dua, Jim Binkley, Suresh Singh

Computer Science Faculty Publications and Presentations

We present an algorithm for detecting IRC-like chat networks that does not rely on Layer 7 payload information. The goal is to extract only those meshes from conventional flows where long-term periodic data is being exchanged between an external server and multiple internal clients. Flow data is passed through a series of filters that reduce the memory requirements needed for final candidate mesh sorting. Final outputs consist of two sorted lists including the fanout list, sorted by the number of client hosts in the mesh, and a secondary list called the evil sort. The latter consists of meshes with any …

Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu

Research Collection School Of Computing and Information Systems

In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …

Accelerating Near-Duplicate Video Matching By Combining Visual Similarity And Alignment Distortion, Hung-Khoon Tan, Xiao Wu, Chong-Wah Ngo, Wan-Lei Zhao

Research Collection School Of Computing and Information Systems

In this paper, we investigate a novel approach to accelerate the matching of two video clips by exploiting the temporal coherence property inherent in the keyframe sequence of a video. Motivated by the fact that keyframe correspondences between near-duplicate videos typically follow certain spatial arrangements, such property could be employed to guide the alignment of two keyframe sequences. We set the alignment problem as an integer quadratic programming problem, where the cost function takes into account both the visual similarity of the corresponding keyframes as well as the alignment distortion among the set of correspondences. The set of keyframe-pairs found …

Traffic Analysis Of Udp-Based Flows In Ourmon, Jim Binkley, Divya Parekh

Computer Science Faculty Publications and Presentations

We present a custom UDP flow tuple with an IP address key and a set of simple related statistical attributes. Attributes are used to calculate a per host metric called the UDP work weight which roughly measures the amount of network noise caused by a host. The work weight is used to produce a near real-time sorted top N report for UDP host tuples. We also present a derived attribute based on an algorithm called the UDP guesstimator. The UDP guesstimator roughly classifies port report hosts into various traffic categories including security threats (DOS/scanning) or P2P hosts based on high …

Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti

Computer Science Faculty Publications

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape models from large-scale sets of point cloud samples efficiently. In this paper, we propose a fast solution for approximating implicit surfaces based on a multi-scale Tikhonov regularization scheme. The optimization of our scheme is formulated into a sparse linear equation system, which can be efficiently solved by factorization methods. Different from traditional approaches, our scheme does not employ auxiliary off-surface points, which not only saves the computational cost but also avoids the problem …

Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara

Electrical & Computer Engineering Faculty Publications

We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been …

Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett

Electrical & Computer Engineering Faculty Publications

Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).

Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …

Apparatus And Method For Using Adaptive Algorithms To Exploit Sparsity In Target Weight Vectors In An Adaptive Channel Equalizer, Richard K. Martin, Robert C. Williamson, William A. Sethares

AFIT Patents

An apparatus and method is disclosed for using adaptive algorithms to exploit sparsity in target weight vectors in an adaptive channel equalizer. An adaptive algorithm comprises a selected value of a prior and a selected value of a cost function. The present invention comprises algorithms adapted for calculating adaptive equalizer coefficients for sparse transmission channels. The present invention provides sparse algorithms in the form of a Sparse Least Mean Squares (LMS) algorithm and a Sparse Constant Modulus Algorithm (CMA) and a Sparse Decision Directed (DD) algorithm.