Computer Sciences Commons^™

Novel Use Of Neural Networks To Identify And Detect Electrical Infrastructure Performance, Evan Pierre Savaria

Computer Science Theses & Dissertations

Electrical grid maintenance and repairs are crucial services that keep America’s lights on. Electrical service providers make it their priority to uphold minimal interruptions to this service. Electricity is essential for modern technology within the home, such as cooking, refrigeration, and hot water. Organizations, such as schools, hospitals, and military bases, cannot properly function or operate without power. When analyzing the current electrical infrastructure, it is evident that considerable components of the power grid are aging and in need of replacement. Additionally, threats and damage continue to occur. These damages occur not only due to simple, single power line failure …

Scalable Parallel Delaunay Image-To-Mesh Conversion For Shared And Distributed Memory Architectures, Daming Feng

Computer Science Theses & Dissertations

Mesh generation is an essential component for many engineering applications. The ability to generate meshes in parallel is critical for the scalability of the entire Finite Element Method (FEM) pipeline. However, parallel mesh generation applications belong to the broader class of adaptive and irregular problems, and are among the most complex, challenging, and labor intensive to develop and maintain. In this thesis, we summarize several years of the progress that we made in a novel framework for highly scalable and guaranteed quality mesh generation for finite element analysis in three dimensions. We studied and developed parallel mesh generation algorithms on …

An Introduction To Declarative Programming In Clips And Prolog, Jack L. Watkin, Adam C. Volk, Saverio Perugini

Computer Science Faculty Publications

We provide a brief introduction to CLIPS—a declarative/logic programming language for implementing expert systems—and PROLOG—a declarative/logic programming language based on first-order, predicate calculus. Unlike imperative languages in which the programmer specifies how to compute a solution to a problem, in a declarative language, the programmer specifies what they what to find, and the system uses a search strategy built into the language. We also briefly discuss applications of CLIPS and PROLOG.

A Machine Learning Approach To Predicting Community Engagement On Social Media During Disasters, Adel Alshehri

USF Tampa Graduate Theses and Dissertations

The use of social media is expanding significantly and can serve a variety of purposes. Over the last few years, users of social media have played an increasing role in the dissemination of emergency and disaster information. It is becoming more common for affected populations and other stakeholders to turn to Twitter to gather information about a crisis when decisions need to be made, and action is taken. However, social media platforms, especially on Twitter, presents some drawbacks when it comes to gathering information during disasters. These drawbacks include information overload, messages are written in an informal format, the presence …

A Novel Method For Intelligent Single Fault Detection Of Bearings Using Sae And Improved D–S Evidence Theory, Jianguang Lu, Huan Zhang, Xianghong Tang

Computer Science Faculty Publications

In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Encoder (SAE) and results fusion of improved Dempster–Shafer evidence theory (D–S). Multi-fault signal compression features of bearings were extracted by SAE on multiple vibration sensors’ data. Data sets were constructed by the extracted compression features to train the Support Vector Machine (SVM) according to the rule of single fault detection (R-SFD) this paper proposed. Fault detection results were obtained by the improved D–S evidence theory, …

Active-Passive Dynamic Consensus Filters For Linear Time-Invariant Multiagent Systems, J. Daniel Peterson, Tansel Yucelen, S. Jagannathan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Active-passive dynamic consensus filters consist of a group of agents, where a subset of these agents is able to observe a quantity of interest (i.e. active agents) and the rest are subject to no observations (i.e. passive agents). Specifically, the objective of these filters is that the states of all agents are required to converge to the weighted average of the set of observations sensed by the active agents. Existing active-passive dynamic consensus filters in the classical sense assume that all agents can be modeled as having single integrator dynamics, which may not always hold in practice. Motivating from this …

Searching Activity Trajectories With Semantics, Li-Hua Yin, Huiwen Liu

PhD Student’s Publications Collection

With the widespread use of smart phones and mobile Internet, social network users have generated massive geo-tagged tweets, photos and videos to form lots of informative trajectories which reveal not only their spatio-temporal dynamics, but also their activities in the physical world. Existing spatial trajectory query studies mainly focus on analyzing the spatio-temporal properties of the users’ trajectories, while leaving the understanding of their activities largely untouched. In this paper, we incorporate the semantics of the activity information embedded in trajectories into query modelling and processing, with the aim of providing end users more informative and meaningful results. To this …

Design And Pilot Testing Of Subgoal Labeled Worked Examples For Five Core Concepts In Cs1, Lauren E. Margulieux, Briana B. Morrison, Adrienne Decker

Computer Science Faculty Publications

Subgoal learning has improved student problem-solving performance in programming, but it has been tested for only oneto-two hours of instruction at a time. Our work pioneers implementing subgoal learning throughout an entire introductory programming course. In this paper we discuss the protocol that we used to identify subgoals for core programming procedures, present the subgoal labels created for the course, and outline the subgoal-labeled instructional materials that were designed for a Java-based course. To examine the effect of subgoal labeled materials on student performance in the course, we compared quiz and exam grades between students who learned using subgoal labels …

Siguria E Të Dhënave Në Rrjetë, Shkëlqim Krasniqi

Theses and Dissertations

Siguria e të dhënave në rrjetë është berë pjesë e rëndesishme e institucioneve dhe bizneseve pasi në rrjetë bëhet shkembimi i informacioneve nepër vende të ndryshme. Qellimi i këtij studimi është që të bejmë një hulumtim global dhe lokal për sigurinë e të dhënave në rrjetë.

Siguria e rrjetit është çdo aktivitet i dizajnuar për të mbrojtur përdorshmërinë dhe integritetin e rrjetit tuaj dhe të dhënave. Ai përfshin teknologjinë harduerike dhe softuerike. Siguria efektive e rrjetit menaxhon qasjen në rrjet. Ajo synon një shumëllojshmëri të kërcënimeve dhe i ndalon ato të hyjnë ose të përhapen në rrjetin tuaj.

Problemi i …

Smart City Lights, Shyhrete Buzaku

Theses and Dissertations

Aktualisht, në të gjithë botën, energji e madhe elektrike konsumohet nga dritat e rrugës, të cilat automatikisht ndizen kur bëhet errësirë dhe automatikisht fiken kur bëhet dritë. Kjo është humbje e madhe e energjisë në të gjithë botën dhe duhet të ndryshohet. Qëllimi kryesor i sistemeve të dritave të zgjuara të rrugëve është që dritat të ndizen kur është e nevojshme dhe dritat të fiket kur nuk nevojiten. Sjellja ideale e sistemit të dritave të zgjuara të rrugëve është të bëhet ndezja e dritave të rrugës gjatë natës në mënyrë efiçiente dhe efektive. Sa herë që dikush kalon pranë dritave …

User Privacy Leakage In Location-Based Mobile Ad Services, Qicheng Lin

School of Computing: Dissertations, Theses, and Student Research

The online advertising ecosystem leverages its massive data collection capability to learn the properties of users for targeted ad deliveries. Many Android app developers include ad libraries in their apps as a way of monetization. These ad libraries contain advertisements from the sell-side platforms, which collect an extensive set of sensitive information to provide more relevant advertisements for their customers. Existing efforts have investigated the increasingly pervasive private data collection of mobile ad networks over time. However, there lacks a measurement study to evaluate the scale of privacy leakage of ad networks across different geographical areas. In this work, we …

Ethical Hacking For Effective Defense (Modules, Labs, And Lectures), Hossain Shahriar

Computer Science and Information Technology Ancillary Materials

Summer 2019 Update: Through a Round Twelve ALG Mini-Grant for Ancillary Materials Creation and Revision, five new modules have been added to this collection:

• Enumeration with Sparta
• Enumeration with Inguma
• Hacking Web Servers with Dirbuster
• Hacking Web Servers with Skipfish
• Hacking Wireless and IoT with Bluehydra

The following set of materials is used in the Textbook Transformation Grants implementation of Ethical Hacking for Effective Defense:

https://oer.galileo.usg.edu/compsci-collections/8/

Topics include:

• TCP/IP Level Attacks
• Port Scanning
• DDoS
• Footprinting and Social Engineering
• Enumeration
• Programming for Security Professionals
• Operating System Vulnerabilities
• Embedded System Security
• Hacking Web Servers
• Hacking Wireless Networks
• Cryptography
• Protecting Networks with …

On Continuous Images Of Ultra-Arcs, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

Any space homeomorphic to one of the standard subcontinua of the Stone-Čech remainder of the real half-line is called an ultra-arc. Alternatively, an ultra-arc may be viewed as an ultracopower of the real unit interval via a free ultrafilter on a countable set. It is known that any continuum of weight is a continuous image of any ultra-arc; in this paper we address the problem of which continua are continuous images under special maps. Here are some of the results we present.

A Shared-Memory Coupled Architecture To Leverage Big Data Frameworks In Prototyping And In-Situ Analytics For Data Intensive Scientific Workflows, Alexander Michael Lemon

Theses and Dissertations

There is a pressing need for creative new data analysis methods whichcan sift through scientific simulation data and produce meaningfulresults. The types of analyses and the amount of data handled by currentmethods are still quite restricted, and new methods could providescientists with a large productivity boost. New methods could be simpleto develop in big data processing systems such as Apache Spark, which isdesigned to process many input files in parallel while treating themlogically as one large dataset. This distributed model, combined withthe large number of analysis libraries created for the platform, makesSpark ideal for processing simulation output.Unfortunately, the filesystem becomes …

Towards Understanding Android System Vulnerabilities: Techniques And Insights, Daoyuan Wu, Debin Gao, Eric K. T. Cheng, Yichen Cao, Jintao Jiang, Robert H. Deng

Research Collection School Of Computing and Information Systems

As a common platform for pervasive devices, Android has been targeted by numerous attacks that exploit vulnerabilities in its apps and the operating system. Compared to app vulnerabilities, systemlevel vulnerabilities in Android, however, were much less explored in the literature. In this paper, we perform the first systematic study of Android system vulnerabilities by comprehensively analyzing all 2,179 vulnerabilities on the Android Security Bulletin program over about three years since its initiation in August 2015. To this end, we propose an automatic analysis framework, upon a hierarchical database structure, to crawl, parse, clean, and analyze vulnerability reports and their publicly …

Event-Triggered Adaptive Distributed State Estimation By Using Active-Passive Sensor Networks, Akhilesh Raj, S. Jagannathan, Tansel Yucelen

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel event-triggered adaptive observer for each node in the heterogeneous sensor networks (HSNs) in order to estimate state vector of an unknown target or process by using the sensed output when the input to the target/ process is unknown. A subset of nodes in the HSN referred to as active nodes, can sense the target periodically, estimate the target state vector by using their adaptive observer and can communicate the estimated state vector of the target with the neighboring nodes including passive nodes only at event triggered instants. The adaptive observer parameters of active nodes are …

Early Information Access To Alleviate Emergency Department Congestion, Anjee Gorkhali

Theses and Dissertations in Business Administration

Alleviating Emergency Department (ED) congestion results in shorter hospital stay which not only reduces the cost of medical procedure but also increase the hospital performance. Length of patient stay is used to determine the hospital performance. Organization Information Processing (OIPT) Theory is used to explain the impact of information access and availability on the information processing need and ability of a hospital. Technical devices such as RFID that works as “Auto Identification tags” is suggested to increase the information availability as well as the information processing capability of the hospitals. This study suggests that the OIPT needs to be further …

Data-Driven Database Education: A Quantitative Study Of Sql Learning In An Introductory Database Course, Andrew C. Von Dollen

Master's Theses

The Structured Query Language (SQL) is widely used and challenging to master. Within the context of lab exercises in an introductory database course, this thesis analyzes the student learning process and seeks to answer the question: ``Which SQL concepts, or concept combinations, trouble students the most?'' We provide comprehensive taxonomies of SQL concepts and errors, identify common areas of student misunderstanding, and investigate the student problem-solving process. We present an interactive web application used by students to complete SQL lab exercises. In addition, we analyze data collected by this application and we offer suggestions for improvement to database lab activities.

Success Factors Impacting Artificial Intelligence Adoption --- Perspective From The Telecom Industry In China, Hong Chen

Theses and Dissertations in Business Administration

As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. …

Simulated Annealing For The Single-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey T. Widjaja, Pieter. Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper studies the Single-Vehicle Cyclic Inventory Routing Problem (SV-CIRP) with the objective of simultaneously minimizing distribution and inventory costs for the customers and maximizing the collected rewards. A subset of customers is selected for the vehicle, including the quantity to be delivered to them. Simulated Annealing (SA) is proposed for solving the problem. Experimental results on 50 benchmark instances show that SA is comparable to the state-of-the-art algorithms. It is able to obtain 12 new best known solutions.

Sensitive Behavior Analysis Of Android Applications On Unrooted Devices In The Wild, Xiaoxiao Tang

Dissertations and Theses Collection (Open Access)

Dynamic analysis is widely used in malware detection, taint analysis, vulnerability detection, and other areas for enhancing the security of Android. Compared to static analysis, dynamic analysis is immune to common code obfuscation techniques and dynamic code loading. Existing dynamic analysis techniques rely on in-lab running environment (e.g., modified systems, rooted devices, or emulators) and require automatic input generators to execute the target app. However, these techniques could be bypassed by anti-analysis techniques that allow apps to hide sensitive behavior when an in-lab environment is detected through predefined heuristics (e.g., IMEI number of the device is invalid). Meanwhile, current input …

Exploiting Mobility For Predictive Urban Analytics & Operations, Kasthuri Jayarajah

Dissertations and Theses Collection (Open Access)

As cities worldwide invest heavily in smart city infrastructure, it invites opportunities for a next wave of urban analytics. Unlike its predecessors, urban analytics applications and services can now be real-time and proactive -- they can (a) leverage situational data from large deployments of connected sensors, (b) capture attributes of a variety of entities that make up the urban fabric (e.g., people and their social relationships, transport nodes, utilities, etc.), and (c) use predictive insights to both proactively optimize urban operations (e.g., HVAC systems in smart buildings, buses in the transportation network, crowd-workers, etc.) and promote smarter policy decisions (e.g., …

Making Sense Of Crowd-Generated Content In Domain-Specific Settings, Agus Sulistya

Dissertations and Theses Collection (Open Access)

The rapid advances of the Web have changed the ways information is distributed and exchanged among individuals and organizations. Various content from different domains are generated daily and contributed by users' daily activities, such as posting messages in a microblog platform, or collaborating in a question and answer site. To deal with such tremendous volume of user generated content, there is a need for approaches that are able to handle the mass amount of available data and to extract knowledge hidden in the user generated content. This dissertation attempts to make sense of the generated content to help in three …

Stressmon: Large Scale Detection Of Stress And Depression In Campus Environment Using Passive Coarse-Grained Location Data, Camellia Zakaria

Dissertations and Theses Collection (Open Access)

The rising mental health illnesses of severe stress and depression is of increasing concern worldwide. Often associated by similarities in symptoms, severe stress can take a toll on a person’s productivity and result in depression if the stress is left unmanaged. Unfortunately, depression can occur without any feelings of stress. With depression growing as a leading cause of disability in economic productivity, there has been a sharp rise in mental health initiatives to improve stress and depression management. To offer such services conveniently and discreetly, recent efforts have focused on using mobile technologies. However, these initiatives usually require users to …

Developing 5gl Concepts From User Interactions, David Stuckless Meyer

Masters Theses

In the fulfilling of the contracts generated in Test Driven Development, a developer could be said to act as a constraint solver, similar to those used by a 5th Generation Language(5GL). This thesis presents the hypothesis that 5GL linguistic mechanics, such as facts, rules and goals, will be emergent in the communications of developer pairs performing Test Driven Development, validating that 5GL syntax is congruent with the ways that practitioners communicate. Along the way, nomenclatures and linguistic patterns may be observed that could inform the design of future 5GL languages.

Promotional Campaigns In The Era Of Social Platforms, Noor E. Abu-El-Rub

Computer Science ETDs

The rise of social media has facilitated the diffusion of information to more easily reach millions of users. While some users connect with friends and organically share information and opinions on social media, others have exploited these platforms to gain influence and profit through promotional campaigns and advertising. The existence of promotional campaigns contributes to the spread of misleading information, spam, and fake news. Thus, these campaigns affect the trustworthiness and reliability of social media and render it as a crowd advertising platform. This dissertation studies the existence of promotional campaigns in social media and explores different ways users and …

A Review On Swarm Intelligence And Evolutionary Algorithms For Solving Flexible Job Shop Scheduling Problems, Kaizhou Gao, Zhiguang Cao, Le Zhang, Zhenghua Chen, Yuyan Han, Quanke Pan

Research Collection School Of Computing and Information Systems

Flexible job shop scheduling problems (FJSP) have received much attention from academia and industry for many years. Due to their exponential complexity, swarm intelligence (SI) and evolutionary algorithms (EA) are developed, employed and improved for solving them. More than 60% of the publications are related to SI and EA. This paper intents to give a comprehensive literature review of SI and EA for solving FJSP. First, the mathematical model of FJSP is presented and the constraints in applications are summarized. Then, the encoding and decoding strategies for connecting the problem and algorithms are reviewed. The strategies for initializing algorithms? population …

Deephunter: A Coverage-Guided Fuzz Testing Framework For Deep Neural Networks, Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Minhui Xue, Hongxu Chen, Yang Liu, Jianjun Zhao, Bo Li, Jianxiong Yin, Simon See

Research Collection School Of Computing and Information Systems

The past decade has seen the great potential of applying deep neural network (DNN) based software to safety-critical scenarios, such as autonomous driving. Similar to traditional software, DNNs could exhibit incorrect behaviors, caused by hidden defects, leading to severe accidents and losses. In this paper, we propose DeepHunter, a coverage-guided fuzz testing framework for detecting potential defects of general-purpose DNNs. To this end, we first propose a metamorphic mutation strategy to generate new semantically preserved tests, and leverage multiple extensible coverage criteria as feedback to guide the test generation. We further propose a seed selection strategy that combines both diversity-based …

Semantic Patches For Java Program Transformation, Hong Jin Kang, Ferdian Thung, Julia Lawall, Gilles Muller, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

Developing software often requires code changes that are widespread and applied to multiple locations.There are tools for Java that allow developers to specify patterns for program matching and source-to-source transformation. However, to our knowledge, none allows for transforming code based on its control-flow context. We prototype Coccinelle4J, an extension to Coccinelle, which is a program transformation tool designed for widespread changes in C code, in order to work on Java source code. We adapt Coccinelle to be able to apply scripts written in the Semantic Patch Language (SmPL), a language provided by Coccinelle, to Java source files. As a case …

A Closer Look Tells More: A Facial Distortion Based Liveness Detection For Face Authentication, Yan Li, Zilong Wang, Yingjiu Li, Robert H. Deng, Binbin Chen, Weizhi Meng, Hui Li

Research Collection School Of Computing and Information Systems

Face authentication is vulnerable to media-based virtual face forgery (MVFF) where adversaries display photos/videos or 3D virtual face models of victims to spoof face authentication systems. In this paper, we propose a liveness detection mechanism, called FaceCloseup, to protect the face authentication on mobile devices. FaceCloseup detects MVFF-based attacks by analyzing the distortion of face regions in a user's closeup facial videos captured by built-in camera on mobile device. It can detect MVFF-based attacks with an accuracy of 99.48%.