Theory and Algorithms Commons^™

Real-Time Anomaly Detection In Full Motion Video, Glenn Konowicz,, Jiang Li, Donnie Self (Ed.)

Electrical & Computer Engineering Faculty Publications

Improvement in sensor technology such as charge-coupled devices (CCD) as well as constant incremental improvements in storage space has enabled the recording and storage of video more prevalent and lower cost than ever before. However, the improvements in the ability to capture and store a wide array of video have required additional manpower to translate these raw data sources into useful information. We propose an algorithm for automatically detecting anomalous movement patterns within full motion video thus reducing the amount of human intervention required to make use of these new data sources. The proposed algorithm tracks all of the objects …

Mathematical Model Development Of Super-Resolution Image Wiener Restoration, Amr H. Yousef, Jiang Li, Mohammad A. Karim

Electrical & Computer Engineering Faculty Publications

In super-resolution (SR), a set of degraded low-resolution (LR) images are used to reconstruct a higher-resolution image that suffers from acquisition degradations. One way to boost SR images visual quality is to use restoration filters to remove reconstructed images artifacts. We propose an efficient method to optimally allocate the LR pixels on the high-resolution grid and introduce a mathematical derivation of a stochastic Wiener filter. It relies on the continuous-discrete-continuous model and is constrained by the periodic and nonperiodic interrelationships between the different frequency components of the proposed SR system. We analyze an end-to-end model and formulate the Wiener filter …

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.

An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang

Research Collection School Of Computing and Information Systems

Text categorization is a significant tool to manage and organize the surging text data. Many text categorization algorithms have been explored in previous literatures, such as KNN, Naive Bayes and Support Vector Machine. KNN text categorization is an effective but less efficient classification method. In this paper, we propose an improved KNN algorithm for text categorization, which builds the classification model by combining constrained one pass clustering algorithm and KNN text categorization. Empirical results on three benchmark corpora show that our algorithm can reduce the text similarity computation substantially and outperform the-state-of-the-art KNN, Naive Bayes and Support Vector Machine classifiers. …

Evolved Design Of A Nonlinear Proportional Integral Derivative (Npid) Controller, Shubham Chopra

Dissertations and Theses

This research presents a solution to the problem of tuning a PID controller for a nonlinear system. Many systems in industrial applications use a PID controller to control a plant or the process. Conventional PID controllers work in linear systems but are less effective when the plant or the process is nonlinear because PID controllers cannot adapt the gain parameters as needed. In this research we design a Nonlinear PID (NPID) controller using a fuzzy logic system based on the Mamdani type Fuzzy Inference System to control three different DC motor systems. This fuzzy system is responsible for adapting the …

Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Many techniques have been recently developed for classification of hyperspectral images (HSI) including support vector machines (SVMs), neural networks and graph-based methods. To achieve good performances for the classification, a good feature representation of the HSI is essential. A great deal of feature extraction algorithms have been developed such as principal component analysis (PCA) and independent component analysis (ICA). Sparse coding has recently shown state-of-the-art performances in many applications including image classification. In this paper, we present a feature extraction method for HSI data motivated by a recently developed sparse coding based image representation technique. Sparse coding consists of a …

Fast Stochastic Wiener Filter For Super-Resolution Image Restoration With Information Theoretic Visual Quality Assessment, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. The reconstructed image suffers from degradations such as blur, aliasing, photo-detector noise and registration and fusion error. Wiener filter can be used to remove artifacts and enhance the visual quality of the reconstructed images. In this paper, we introduce a new fast stochastic Wiener filter for SR reconstruction and restoration that can be implemented efficiently in the frequency domain. Our derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering …

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 …

Mobile Phone Graph Evolution: Findings, Model And Interpretation, Siyuan Liu, Lei Li, Christos Faloutsos, Lionel M. Ni

LARC Research Publications

What are the features of mobile phone graph along the time? How to model these features? What are the interpretation for the evolutional graph generation process? To answer the above challenging problems, we analyze a massive who-call-whom networks as long as a year, gathered from records of two large mobile phone communication networks both with 2 million users and 2 billion of calls. We examine the calling behavior distribution at multiple time scales (e.g. day, week, month and quarter), and find that the distribution is not only skewed with a heavy tail, but also changing at different time scales. How …

Identifying Effort Estimation Factors For Corrective Maintenance In Object-Oriented Systems, Michael J. Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research identifies factors that impact software maintenance effort by exploring the decision-making process of expert estimators of corrective maintenance projects by using qualitative methods to identify the factors that they use in deriving estimates. We implement a technique called causal mapping, which allows us to identify the cognitive links between the information that estimators use, and the estimates that they produce based on that information. Results suggest that a total of 17 factors may be relevant for corrective maintenance effort estimation, covering constructs related to developers, code, defects, and environment. When these factors are rank-ordered, they demonstrate that some …

Quantification Of Stochastic Uncertainty Propagation For Monte Carlo Depletion Methods In Reactor Analysis, Quentin Thomas Newell

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Monte Carlo method provides powerful geometric modeling capabilities for large problem domains in 3-D; therefore, the Monte Carlo method is becoming popular for 3-D fuel depletion analyses to compute quantities of interest in spent nuclear fuel including isotopic compositions. The Monte Carlo approach has not been fully embraced due to unresolved issues concerning the effect of Monte Carlo uncertainties on the predicted results.

Use of the Monte Carlo method to solve the neutron transport equation introduces stochastic uncertainty in the computed fluxes. These fluxes are used to collapse cross sections, estimate power distributions, and deplete the fuel within depletion …

Exploring Tweets Normalization And Query Time Sensitivity For Twitter Search, Zhongyu Wei, Wei Gao, Lanjun Zhou, Binyang Li, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

This paper presents our work for the Realtime Adhoc Task of TREC 2011 Microblog Track. Microblog texts like tweets are generally characterized by the inclusion of a large proportion of irregular expressions, such as ill-formed words, which can lead to significant mismatch between query terms and tweets. In addition, Twitter queries are distinguished from Web queries with many unique characteristics, one of which reflects the clearly distinct temporal aspects of Twitter search behavior. In this study, we deal with the first problem by normalizing tweet texts and the second by capturing the temporal characteristics of topic. We divided topics into …

Beyond Search: Event-Driven Summarization For Web Videos, Richard Hong, Jinhui Tang, Hung-Khoon Tan, Chong-Wah Ngo, Shuicheng Yan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The explosive growth of Web videos brings out the challenge of how to efficiently browse hundreds or even thousands of videos at a glance. Given an event-driven query, social media Web sites usually return a large number of videos that are diverse and noisy in a ranking list. Exploring such results will be time-consuming and thus degrades user experience. This article presents a novel scheme that is able to summarize the content of video search results by mining and threading "key" shots, such that users can get an overview of main content of these videos at a glance. The proposed …

Isomorph-Free Generation Of 2-Connected Graphs With Applications, Derrick Stolee

School of Computing: Technical Reports

Many interesting graph families contain only 2-connected graphs, which have ear decompositions. We develop a technique to generate families of unlabeled 2-connected graphs using ear augmentations and apply this technique to two problems. In the first application, we search for uniquely Kr-saturated graphs and find the list of uniquely K4-saturated graphs on at most 12 vertices, supporting current conjectures for this problem. In the second application, we verify the Edge Reconstruction Conjecture for all 2-connected graphs on at most 12 vertices. This technique can be easily extended to more problems concerning 2-connected graphs.

Roaming Region For Delaunay Triangulation, Romas James Hada

UNLV Theses, Dissertations, Professional Papers, and Capstones

Delaunay graphs have been used in CAD/CAM, sensor network and geographic information systems. We investigate the reliability properties of nodes in Delaunay graphs. For measuring the reliability we formulate the concept of roaming-region for nodes. A node v with large roaming-region r(v) such that v is positioned near the center of r(v) is identified as a reliable node. We develop algorithms for constructing roaming-regions and present an implementation of the proposed algorithm in the Java programming language.

Improved Algorithms For Ear-Clipping Triangulation, Bartosz Kajak

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider the problem of improving ear-slicing algorithm for triangulating a simple polygon. We propose two variations of ear-slicing technique for generating “good-quality” triangulation. The first approach is based on searching for the best triangle along the boundary. The second approach considers polygon partitioning on a pre-process before applying the ear-slicing. Experimental investigation reveals that both approaches yield better quality triangulation than the standard ear-slicing method.

Structure And Randomness Of The Discrete Lambert Map, Jingjing Chen, Mark Lotts

Mathematical Sciences Technical Reports (MSTR)

We investigate the structure and cryptographic applications of the Discrete Lambert Map (DLM). The mapping is closely related to the Discrete Log Problem, but has received far less attention since it is considered to be a more complicated map that is likely even harder to invert. However, this mapping is quite important because it underlies the security of the ElGamal Digital Signature Scheme. Using functional graphs induced by this mapping, we were able to find non-random properties that could potentially be used to exploit the ElGamal DSS.

The Square Discrete Exponentiation Map, A Wood

Mathematical Sciences Technical Reports (MSTR)

We will examine the square discrete exponentiation map and its properties. The square discrete exponentiation map is a variation on a commonly seen problem in cryptographic algorithms. This paper focuses on understanding the underlying structure of the functional graphs generated by this map. Specifically, this paper focuses on explaining the in-degree of graphs of safe primes, which are primes of the form p = 2q + 1, where q is also prime.

Image Processing – I: Pointing And Target Selection Of Object Using Color Detection Algorithm Through Dsp Processor Tms320c6711, Waseem Ahmed, M. Irfan, Mr. Muzammil, Mr. Yaseen

International Conference on Information and Communication Technologies

In the field of robotic and image vision technologies, the embedded computing and optimization of the image processing algorithm is quite significant in order to provide the real time processing. In the current era, for making the real time system for such high extensive computation and processing for providing the high speed and real time standalone system, several industrial giants continuously providing the solutions which are in the form of dedicated DSP processors and generalized FPGAs. Beside such high speed processor implementation, the image processing based algorithm plays significant role in machine vision based solution for industries, robotic and field …

Network Security: Privacy-Preserving Data Publication: A Review On “Updates” In Continuous Data Publication, Adeel Anjum, Guillaume Raschia

International Conference on Information and Communication Technologies

Preserving the privacy of individuals while publishing their relevant data has been an important problem. Most of previous works in privacy preserving data publication focus on one time, static release of datasets. In multiple publications however, where data is published multiple times, these techniques are unable to ensure privacy of the concerned individuals as just joining either of the releases could result in identity disclosure. In this work, we tried to investigate the major findings in the scenario of continuous data publication, in which the data is not only published multiple times but also modified with INSERTS, UPDATES and DELETE …