Engineering Commons^™

Bayesian Calibration Tool, Sveinn Palsson, Martin Hunt, Alejandro Strachan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Fitting a model to data is common practice in many fields of science. The models may contain unknown parameters and often, the goal is to obtain good estimates of them. A variety of methods have been developed for this purpose. They often differ in complexity, efficiency and accuracy and some may have very limited applications. Bayesian inference methods have recently become popular for the purpose of calibrating model's parameters. The way they treat unknown quantities is completely different from any classical methods. Even though the unknown quantity is a constant, it is treated as a random variable and the desired …

Testing The Forensic Soundness Of Forensic Examination Environments On Bootable Media, Ahmed F.A.L. Mohamed, Andrew Marrington, Farkhund Iqbal, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

In this work we experimentally examine the forensic soundness of the use of forensic bootable CD/DVDs as forensic examination environments. Several Linux distributions with bootable CD/DVDs which are marketed as forensic examination environments are used to perform a forensic analysis of a captured computer system. Before and after the bootable CD/DVD examination, the computer system's hard disk is removed and a forensic image acquired by a second system using a hardware write blocker. The images acquired before and after the bootable CD/DVD examination are hashed and the hash values compared. Where the hash values are inconsistent, a differential analysis is …

Preliminary Forensic Analysis Of The Xbox One, Jason Moore, Ibrahim Baggili, Andrew Marrington, Armindo Rodrigues

Electrical & Computer Engineering and Computer Science Faculty Publications

Video game consoles can no longer be viewed as just gaming consoles but rather as full multimedia machines, capable of desktop computer-like performance. The past has shown that game consoles have been used in criminal activities such as extortion, identity theft, and child pornography, but with their ever-increasing capabilities, the likelihood of the expansion of criminal activities conducted on or over the consoles increases. This research aimed to take the initial step of understanding the Xbox One, the most powerful Microsoft console to date. We report the outcome of conducting a forensic examination of the Xbox One, and we provide …

An Adaptive Educational Game To Help Students Learn How To Solve Systems Of Linear Equations, Wang Zhang

Theses and Dissertations

Educational games have been proven to be effective in developing problem solving skills in well-defined domain, such as Math and Physics. In this thesis, an educational game called Matrix was developed to foster problem solving skills in the domain of linear algebra, particularly solving a system of linear equations. Matrix is an adaptive educational game that uses intelligent tutoring modules to guide the student's learning process and provide feedback based on the student's performance. These modules are domain module, student module, pedagogical module and presentation module. The domain module contains all the concepts the student needs to learn and an …

A Mathematical Model And Metaheuristics For Time Dependent Orienteering Problem, Aldy Gunawan, Zhi Yuan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper presents a generalization of the Orienteering Problem, the Time-Dependent Orienteering Problem (TDOP) which is based on the real-life application of providing automatic tour guidance to a large leisure facility such as a theme park. In this problem, the travel time between two nodes depends on the time when the trip starts. We formulate the problem as an integer linear programming (ILP) model. We then develop various heuristics in a step by step fashion: greedy construction, local search and variable neighborhood descent, and two versions of iterated local search. The proposed metaheuristics were tested on modified benchmark instances, randomly …

Modeling And Development Of Human Interface For Pedestrian Simulator, Romesh Khaddar

UNLV Theses, Dissertations, Professional Papers, and Capstones

According to Traveler opinion and perception survey of 2005, 107.4 million Americans use walking as regular mode of travel, which amounts to 51% of American population. In 2009, 4092 pedestrian fatalities have been reported nationwide with a fatality rate of 1.33 which totals 59,000 crashes. Also, pedestrians are over represented in crash data by accounting more than 12% of fatalities but on 10.9% of trips. This makes a perfect case for understanding the causes behind such statistics, calling for a continuous research on pedestrians walking behavior and their interactions with surroundings.

Current research in pedestrian simulation focuses on surveys and …

Gate Monte Carlo Simulations In A Cloud Computing Environment, Blake Austin Rowedder

UNLV Theses, Dissertations, Professional Papers, and Capstones

The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications, e.g. PET, SPECT, CT, radiotherapy, and hadron therapy. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time. By accessing the powerful computational resources of a cloud computing environment, GATE's runtime can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulations using a commercial cloud …

A Comparative Study Of Underwater Robot Path Planning Algorithms For Adaptive Sampling In A Network Of Sensors, Sreeja Banerjee

School of Computing: Dissertations, Theses, and Student Research

Monitoring lakes, rivers, and oceans is critical to improving our understanding of complex large-scale ecosystems. We introduce a method of underwater monitoring using semi-mobile underwater sensor networks and mobile underwater robots in this thesis. The underwater robots can move freely in all dimension while the sensor nodes are anchored to the bottom of the water column and can move only up and down along the depth of the water column. We develop three different algorithms to optimize the path of the underwater robot and the positions of the sensors to improve the overall quality of sensing of an area of …

Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma

UNLV Theses, Dissertations, Professional Papers, and Capstones

With enormous amount of linguistic data present on web, text analysis has become one of the major fields of interest today. This field includes sentiment analysis, information retrieval, text document classification, knowledge based modeling, content similarity measure, data clustering, words prediction/correction, decision making etc. Managing and processing such data has vital importance. The field being quite broad, our focus is mainly on transportation related social media(Twitter) data extraction, text categorization/classification which can be further sub-divided into concept discovery, word sense disambiguation and sentiment analysis to analyze performance of existing transportation system worldwide. Concept discovery is the method of extracting the …

An Empirical Study Of Off-Line Configuration And On-Line Adaptation In Operator Selection, Zhi Yuan, Stephanus Daniel Handoko, Duc Thien Nguyen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Automating the process of finding good parameter settings is important in the design of high-performing algorithms. These automatic processes can generally be categorized into off-line and on-line methods. Off-line configuration consists in learning and selecting the best setting in a training phase, and usually fixes it while solving an instance. On-line adaptation methods on the contrary vary the parameter setting adaptively during each algorithm run. In this work, we provide an empirical study of both approaches on the operator selection problem, explore the possibility of varying parameter value by a non-adaptive distribution tuned off-line, and incorporate the off-line with on-line …

Integrating Visual Mnemonics And Input Feedback With Passphrases To Improve The Usability And Security Of Digital Authentication, Kevin Juang

All Dissertations

The need for both usable and secure authentication is more pronounced than ever before. Security researchers and professionals will need to have a deep understanding of human factors to address these issues. Due to their ubiquity, recoverability, and low barrier of entry, passwords remain the most common means of digital authentication. However, fundamental human nature dictates that it is exceedingly difficult for people to generate secure passwords on their own. System-generated random passwords can be secure but are often unusable, which is why most passwords are still created by humans. We developed a simple system for automatically generating mnemonic phrases …

Software Porting Of A 3d Reconstruction Algorithm To Razorcam Embedded System On Chip, Kevin Curtis Gunn

Graduate Theses and Dissertations

A method is presented to calculate depth information for a UAV navigation system from Keypoints in two consecutive image frames using a monocular camera sensor as input and the OpenCV library. This method was first implemented in software and run on a general-purpose Intel CPU, then ported to the RazorCam Embedded Smart-Camera System and run on an ARM CPU onboard the Xilinx Zynq-7000. The results of performance and accuracy testing of the software implementation are then shown and analyzed, demonstrating a successful port of the software to the RazorCam embedded system on chip that could potentially be used onboard a …

Reducing Carbon Emission Of Ocean Shipments By Optimizing Container Size Selection, Edwin Lik Ming Chong, Nang Laik Ma, Kar Way Tan

Research Collection School Of Computing and Information Systems

Human’s impact on earth through global warming is more or less an accepted fact. Ocean freight is estimated to contribute 4-5% of global carbon emissions and manufacturing companies can aid in reducing this amount. Many companies that ship goods through full container loads do not have the capabilities to ensure the containers they are using minimizes their carbon footprint. One of the reasons is the choice of non-ideal container sizes for their shipments. This paper provides a mathematical model to minimize companies’ shipping carbon footprints by selecting the ideal container sizes appropriate for their shipment volumes. Using data from a …

Hybrid Metaheuristics For Solving The Quadratic Assignment Problem And The Generalized Quadratic Assignment Problem, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper presents a hybrid metaheuristic for solving the Quadratic Assignment Problem (QAP). The proposed algorithm involves using the Greedy Randomized Adaptive Search Procedure (GRASP) to construct an initial solution, and then using a hybrid Simulated Annealing and Tabu Search (SA-TS) algorithm to further improve the solution. Experimental results show that the hybrid metaheuristic is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time. The proposed algorithm is extended to solve the Generalized Quadratic Assignment Problem (GQAP), with an emphasis on modelling and solving a practical problem, namely an examination timetabling problem. We found that …

Diversity-Oriented Bi-Objective Hyper-Heuristics For Patrol Scheduling, Mustafa Misir, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The patrol scheduling problem is concerned with assigning security teams to different stations for distinct time intervals while respecting a limited number of contractual constraints. The objective is to minimise the total distance travelled while maximising the coverage of the stations with respect to their security requirement levels. This paper introduces a hyper-heuristic strategy focusing on generating diverse solutions for a bi-objective patrol scheduling problem. While a variety of hyper-heuristics have been applied to a large suite of problem domains usually in the form of single-objective optimisation, we suggest an alternative approach for solving the patrol scheduling problem with two …

Interpolating Beach Profile Data Using Linear And Non-Linear Functions, Lance Calloway Croft

USF Tampa Graduate Theses and Dissertations

ABSTRACT

Beach and nearshore surveys are conducted in a variety of ways, the most commonly used being the level-and-transit method; because it is inexpensive, time conducive and highly accurate. Specifically, beach surveys are conducted to better understand cross-shore, long-shore sediment transport processes, as well as to quantify volume changes, which are used to evaluate beach performance. In this study, a section of the beach on Sand Key, FL was surveyed using rod-and-transit. In addition to the commonly used linear data analysis, a non-linear analysis was conducted using NURBS (Non-Uniform Rational B-Splines).

Survey data was collected within a short time window …

Is Your Ontology As Hard As You Think? Rewriting Ontologies Into Simpler Dls, David Carral, Cristina Feier, Ana Armas Romero, Bernardo Cuenca-Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

We investigate cases where an ontology expressed in a seemingly hard DL can be polynomially reduced to one in a simpler logic, while preserving reasoning outcomes for classification and fact entailment. Our transformations target the elimination of inverse roles, universal and existential restrictions, and in the best case allow us to rewrite the given ontology into one of the OWL 2 profiles. Even if an ontology cannot be fully rewritten into a profile, in many cases our transformations allow us to exploit further optimisation techniques. Moreover, the elimination of some out-of-profile axioms can improve the performance of modular reasoners, such …

A Knowledge Discovery Approach For The Detection Of Power Grid State Variable Attacks, Nathan Wallace

Doctoral Dissertations

As the level of sophistication in power system technologies increases, the amount of system state parameters being recorded also increases. This data not only provides an opportunity for monitoring and diagnostics of a power system, but it also creates an environment wherein security can be maintained. Being able to extract relevant information from this pool of data is one of the key challenges still yet to be obtained in the smart grid. The potential exists for the creation of innovative power grid cybersecurity applications, which harness the information gained from advanced analytics. Such analytics can be based on the extraction …

Accurate Local Estimation Of Geo-Coordinates For Social Media Posts, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Computer Science and Engineering Faculty Publications

Associating geo-coordinates with the content of social media posts can enhance many existing applications and services and enable a host of new ones. Unfortunately, a majority of social media posts are not tagged with geo-coordinates. Even when location data is available, it may be inaccurate, very broad or sometimes fictitious. Contemporary location estimation approaches based on analyzing the content of these posts can identify only broad areas such as a city, which limits their usefulness. To address these shortcomings, this paper proposes a methodology to narrowly estimate the geo-coordinates of social media posts with high accuracy. The methodology relies solely …

Paxos Based Directory Updates For Geo-Replicated Cloud Storage, Srivathsava Rangarajan

Open Access Theses

Modern cloud data stores (e.g., Spanner, Cassandra) replicate data across geographically distributed data centers for availability, redundancy and optimized latencies.^ An important class of cloud data stores involves the use of directories to track the location of individual data objects. Directory-based datastores allow flexible data placement, and the ability to adapt placement in response to changing workload dynamics. However, a key challenge is maintaining and updating the directory state when replica placement changes.^ In this thesis, we present the design and implementation of a system to address the problem of correctly updating these directories. Our system is built around JPaxos, …

Tracking Dynamic Construction Objects ---A Key Node Modeling Approach Using Color-Depth Cameras, Chenxi Yuan

Open Access Theses

A construction site presents a dynamic scenario. Locations of multiple objects are continuously changing and a lot of objects enter and exit the site in high frequencies. Meanwhile a construction activity consists of a large amount of stochastic operations, many uncertainties occur when making decisions. Believing that detecting, locating and tracking dynamic construction objects in real time improve construction productivity and enhance construction safety, a large number of studies have applied a variety of sensing technologies to construction sites. Hybrid image-point cloud sensing technologies, such as color-depth cameras, have a great potential in achieving real time object recognition and tracking …

Click-Through-Based Cross-View Learning For Image Search, Yingwei Pan, Ting Yao, Tao Mei, Houqiang Li, Chong-Wah Ngo, Yong Rui

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. Existing search engines highly depend on surrounding texts for ranking images, or leverage the query-image pairs annotated by human labelers to train a series of ranking functions. However, there are two major limitations: 1) the surrounding texts are often noisy or too few to accurately describe the image content, and 2) the human annotations are resourcefully expensive and thus cannot be scaled up. We demonstrate in this paper that the above two fundamental challenges can be mitigated by jointly exploring the …

Creating Autonomous Adaptive Agents In A Real-Time First-Person Shooter Computer Game, Di Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Games are good test-beds to evaluate AI methodologies. In recent years, there has been a vast amount of research dealing with real-time computer games other than the traditional board games or card games. This paper illustrates how we create agents by employing FALCON, a self-organizing neural network that performs reinforcement learning, to play a well-known first-person shooter computer game called Unreal Tournament. Rewards used for learning are either obtained from the game environment or estimated using the temporal difference learning scheme. In this way, the agents are able to acquire proper strategies and discover the effectiveness of different weapons without …

El-Ifying Ontologies, David Carral, Cristina Feier, Bernardo Cuenca Grau, Pascal Hitzler, Ian Horrocks

Computer Science and Engineering Faculty Publications

The OWL 2 profiles are fragments of the ontology language OWL 2 for which standard reasoning tasks are feasible in polynomial time. Many OWL ontologies, however, contain a typically small number of out-of-profile axioms, which may have little or no influence on reasoning outcomes. We investigate techniques for rewriting axioms into the EL and RL profiles of OWL 2. We have tested our techniques on both classification and data reasoning tasks with encouraging results.

Ultimate Codes: Near-Optimal Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Chong Wang, Ke Zhou, Yuhong Zhao

School of Computing: Technical Reports

As modern storage systems have grown in size and complexity, RAID-6 is poised to replace RAID-5 as the dominant form of RAID architectures due to its ability to protect against double disk failures. Many excellent erasure codes specially designed for RAID-6 have emerged in recent years. However, all of them have limitations. In this paper, we present a class of near perfect erasure codes for RAID-6, called the Ultimate codes. These codes encode, update and decode either optimally or nearly optimally, regardless of what the code length is. This implies that utilizing these codes we can build highly efficient and …

S-Code: Lowest Density Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Ke Zhou, Yuhong Zhao, Chong Wang

School of Computing: Technical Reports

RAID, a storage architecture designed to exploit I/O parallelism and provide data reliability, has been deployed widely in computing systems as a storage building block. In large scale storage systems, in particular, RAID-6 is gradually replacing RAID-5 as the dominant form of disk arrays due to its capability of tolerating concurrent failures of any two disks. MDS (maximum distance separable) array codes are the most popular erasure codes that can be used for implementing RAID-6, since they enable optimal storage efficiency and efficient encoding and decoding algorithms. In this paper, we propose a new class of MDS array codes called …

Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu

Research Collection School Of Computing and Information Systems

Influential user can play a crucial role in online social networks. This paper documents an empirical study aiming at exploring the effects of influential users in the context of music social network. To achieve this goal, music diffusion graph is developed to model how information propagates over network. We also propose a heuristic method to measure users' influences. Using the real data from Last. fm, our empirical test demonstrates key effects of influential users and reveals limitations of existing influence identification/characterization schemes.

Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh

Faculty Publications

No abstract provided.

Grounded Ontology – A Proposed Methodology For Emergent Ontology Engineering, Syed Irfan Nabi, Zaheeruddin Asif

Business Review

This research posits that a domain ontology developed using text-coding technique contributes in conceptualizing and representing state-of-the-art as given by published research in a particular domain. The motivation behind this research is to provide means for creating a better understanding among the researchers through ontology that would present a clearer picture of any domain of interest. However, a general observation on ontology engineering methods is the domination of personal perspective of ontology developer and/or expert in the resultant ontology. Current ontology engineering methods bestow a primary role to ontology developer. Ontology thus developed is heavily biased towards the domain expert’s …

Understanding The Paradigm Shift To Computational Social Science In The Presence Of Big Data, Ray M. Chang, Robert J. Kauffman, Young Ok Kwon

Research Collection School Of Computing and Information Systems

The era of big data has created new opportunities for researchers to achieve high relevance and impact amid changes and transformations in how we study social science phenomena. With the emergence of new data collection technologies, advanced data mining and analytics support, there seems to be fundamental changes that are occurring with the research questions we can ask, and the research methods we can apply. The contexts include social networks and blogs, political discourse, corporate announcements, digital journalism, mobile telephony, home entertainment, online gaming, financial services, online shopping, social advertising, and social commerce. The changing costs of data collection and …