Ready Raider One: Exploring The Misuse Of Cloud Gaming Services,
2022
Old Dominion University
Ready Raider One: Exploring The Misuse Of Cloud Gaming Services, Guannan Liu, Daiping Liu, Shuai Hao, Xing Gao, Kun Sun, Haining Wang
Computer Science Faculty Publications
Cloud gaming has become an emerging computing paradigm in recent years, allowing computer games to offload complex graphics and logic computation to the cloud. To deliver a smooth and high-quality gaming experience, cloud gaming services have invested abundant computing resources in the cloud, including adequate CPUs, top-tier GPUs, and high-bandwidth Internet connections. Unfortunately, the abundant computing resources offered by cloud gaming are vulnerable to misuse and exploitation for malicious purposes. In this paper, we present an in-depth study on security vulnerabilities in cloud gaming services. Specifically, we reveal that adversaries can purposely inject malicious programs/URLs into the cloud gaming services …
Hard Real-Time Linux On A Raspberry Pi For 3d Printing,
2022
San Jose State University
Hard Real-Time Linux On A Raspberry Pi For 3d Printing, Alvin Nguyen
Master's Projects
The project presents how a Raspberry Pi with hard real-time enabled Linux can control stepper motors to operate the kinematics of a 3D (three-dimensional) printer. The consistent performance of the Raspberry Pi with the PREEMPT-RT (real-time) patch can satisfy real hard-time requirements for 3D printing kinematics, without introducing dedicated microcontrollers. The Klipper 3D printer firmware enables one of the Raspberry Pi processors to act as the Klipper MCU, the primary controller for the hardware components. This project introduces a software implementation of the control logic for controlling the stepper motors, which utilizes the PCA9685 pwm driver and TB6612 motor drivers …
Evaluation Of Continuous Power-Down Schemes,
2022
University of Nevada, Las Vegas
Evaluation Of Continuous Power-Down Schemes, James Andro-Vasko, Wolfgang Bein
Computer Science Faculty Research
We consider a power-down system with two states—“on” and “off”—and a continuous set of power states. The system has to respond to requests for service in the “on” state and, after service, the system can power off or switch to any of the intermediate power-saving states. The choice of states determines the cost to power on for subsequent requests. The protocol for requests is “online”, which means that the decision as to which intermediate state (or the off-state) the system will switch has to be made without knowledge of future requests. We model a linear and a non-linear system, and …
A Practical Approach To Automated Software Correctness Enhancement,
2021
New Jersey Institute of Technology
A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko
Dissertations
To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …
Dynamic Resource Management Of Fog-Cloud Computing For Iot Support,
2021
San Jose State University
Dynamic Resource Management Of Fog-Cloud Computing For Iot Support, Mariia Surmenok
Master's Projects
The internet of things (IoT) is an integrated part of contemporary life. It includes wearable devices, such as smart watches and cell phones, as well as sensors for Smart City. Fog computing can improve the efficiency and battery life of IoT devices by offloading tasks to fog cloud. It is important to have fog clusters near the IoT device for faster data offload. The goal of this project is to develop dynamic resource allocation for on-demand fog computing cluster to efficiently deploy tasks from IoT. This report studies the different research papers about the current state of resource management in …
Deep Learning Strategies For Pool Boiling Heat Flux Prediction Using Image Sequences,
2021
University of Arkansas, Fayetteville
Deep Learning Strategies For Pool Boiling Heat Flux Prediction Using Image Sequences, Connor Heo
Graduate Theses and Dissertations
The understanding of bubble dynamics during boiling is critical to the design of advanced heater surfaces to improve the boiling heat transfer. The stochastic bubble nucleation, growth, and coalescence processes have made it challenging to obtain mechanistic models that can predict boiling heat flux based on the bubble dynamics. Traditional boiling image analysis relies on the extraction of the dominant physical quantities from the images and is thus limited to the existing knowledge of these quantities. Recently, machine-learning-aided analysis has shown success in boiling crisis detection, heat flux prediction, real-time image analysis, etc., whereas most of the existing studies are …
Component Damage Source Identification For Critical Infrastructure Systems,
2021
University of Arkansas, Fayetteville
Component Damage Source Identification For Critical Infrastructure Systems, Nathan Davis
Graduate Theses and Dissertations
Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties …
Millipyde: A Cross-Platform Python Framework For Transparent Gpu Acceleration,
2021
California Polytechnic State University, San Luis Obispo
Millipyde: A Cross-Platform Python Framework For Transparent Gpu Acceleration, James B. Asbury
Master's Theses
The prevalence of general-purpose GPU computing continues to grow and tackle a wider variety of problems that benefit from GPU-acceleration. This acceleration often suffers from a high barrier to entry, however, due to the complexity of software tools that closely map to the underlying GPU hardware, the fast-changing landscape of GPU environments, and the fragmentation of tools and languages that only support specific platforms. Because of this, new solutions will continue to be needed to make GPGPU acceleration more accessible to the developers that can benefit from it. AMD’s new cross-platform development ecosystem ROCm provides promise for developing applications and …
Memory Forensics Comparison Of Apple M1 And Intel Architecture Using Volatility Framework,
2021
Louisiana State University and Agricultural and Mechanical College
Memory Forensics Comparison Of Apple M1 And Intel Architecture Using Volatility Framework, Joshua Duke
LSU Master's Theses
Memory forensics allows an investigator to get a full picture of what is occurring on-device at the time that a memory sample is captured and is frequently used to detect and analyze malware. Malicious attacks have evolved from living on disk to having persistence mechanisms in the volatile memory (RAM) of a device and the information that is captured in memory samples contains crucial information for full forensic analysis by cybersecurity professionals. Recently, Apple unveiled computers containing a custom designed system on a chip (SoC) called the M1 that is based on ARM architecture. Our research focused on the differences …
System Design And Optimization For Efficient Flash-Based Caching In Data Centers,
2021
Louisiana State University and Agricultural and Mechanical College
System Design And Optimization For Efficient Flash-Based Caching In Data Centers, Jian Liu
LSU Doctoral Dissertations
Modern data centers are the backbone of today’s Internet-based services and applications. With the explosive growth of the Internet data and a wider range of data-intensive applications being deployed, it is increasingly challenging for data centers to satisfy the ever-increasing demand for high-quality data services. To relieve the heavy burden on data center systems and accelerate data processing, a popular cost-efficient solution is to deploy high-speed, large-capacity flash-based cache systems. However, we are facing multiple critical challenges from device hardware, systems, to application workloads. In this dissertation, we focus on designing highly efficient caching solutions to cope with the explosive …
The Negative Effects Of Cyberbullying Among Secondary School Adolescents In Tanzania,
2021
University of British Columbia
The Negative Effects Of Cyberbullying Among Secondary School Adolescents In Tanzania, Hezron Zacharia Onditi, Jennifer Shapka
Journal of Humanities and Social Sciences
Cyberbullying and its associated consequences on children and adolescents has recently become a problem of global concern. Using phenomenological research design, this study explores the negative effects of cyberbullying on Tanzanian secondary school female and male adolescents. A total of 20 adolescents (50% female) in secondary schools (Form I to Form IV) who identified themselves as victims of cyberbullying were involved in the interview to share their lived experiences on the negative effects of cyberbullying. From thematic analysis, results indicated that, similar to their counterpart adolescents in the developed countries, Tanzanian female and male adolescents have experienced emotional, social, cognitive, …
Automated Discovery Of Network Cameras In Heterogeneous Web Pages,
2021
Purdue University
Automated Discovery Of Network Cameras In Heterogeneous Web Pages, Ryan Dailey, Aniesh Chawla, Andrew Liu, Sripath Mishra, Ling Zhang, Josh Majors, Yung-Hisang Lu, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
Reduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer real-time visual data that can be used for studying traffic patterns, emergency response, security, and other applications. Although many sources of Network Camera data are available, collecting the data remains difficult due to variations in programming interface and website structures. Previous solutions rely on manually parsing the target website, taking many hours to complete. We create a general and automated solution for aggregating Network Camera data spread across thousands of uniquely …
Building A More Sustainable And Accessible Internet: Lightweight Web Design With Html And Css,
2021
San Jose State University
Building A More Sustainable And Accessible Internet: Lightweight Web Design With Html And Css, Chelsea Thompto
Assignment Prompts
While the internet has great potential to bring people together, if the internet was a country, it would be the 7th largest energy consumer on the planet. This is set to increase in years to come moving the internet even higher on this list to become the 4th largest energy consumer if it were to be a country. So, as artists and digital citizens it is imperative that we understand how to create and display the content we produce online in ways that are sustainable and accessible.
This assignment, while slated for Art 109, may be slotted into an earlier …
Neural Architecture Search Of Spd Manifold Networks,
2021
Singapore Management University
Neural Architecture Search Of Spd Manifold Networks, R.S. Sukthanker, Zhiwu Huang, S. Kumar, E. G. Endsjo, Y. Wu, Gool L. Van
Research Collection School Of Computing and Information Systems
In this paper, we propose a new neural architecture search (NAS) problem of Symmetric Positive Definite (SPD) manifold networks, aiming to automate the design of SPD neural architectures. To address this problem, we first introduce a geometrically rich and diverse SPD neural architecture search space for an efficient SPD cell design. Further, we model our new NAS problem with a one-shot training process of a single supernet. Based on the supernet modeling, we exploit a differentiable NAS algorithm on our relaxed continuous search space for SPD neural architecture search. Statistical evaluation of our method on drone, action, and emotion recognition …
Material Detection With Thermal Imaging And Computer Vision: Potentials And Limitations,
2021
University of Arkansas, Fayetteville
Material Detection With Thermal Imaging And Computer Vision: Potentials And Limitations, Jared Poe
Graduate Theses and Dissertations
The goal of my masters thesis research is to develop an affordable and mobile infraredbased environmental sensoring system for the control of a servo motor based on material identification. While this sensing could be oriented towards different applications, my thesis is particularly interested in material detection due to the wide range of possible applications in mechanical engineering. Material detection using a thermal mobile camera could be used in manufacturing, recycling or autonomous robotics. For my research, the application that will be focused on is using this material detection to control a servo motor by identifying and sending control inputs based …
Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning,
2021
University of Arkansas, Fayetteville
Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel
Graduate Theses and Dissertations
This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …
Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System.,
2021
University of Arkansas, Fayetteville
Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley
Graduate Theses and Dissertations
Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …
Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation,
2021
University of Arkansas, Fayetteville
Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman
Graduate Theses and Dissertations
Expert recommendation is the process of identifying individuals who have the appropriate knowledge and skills to achieve a specific task. It has been widely used in the educational environment mainly in the hiring process, paper-reviewer assignment, and assembling conference program committees. In this research, we highlight the problem of diversity and fair representation of underrepresented groups in expertise recommendation, factors that current expertise recommendation systems rarely consider. We introduce a novel way to model experts in academia by considering demographic attributes in addition to skills. We use the h-index score to quantify skills for a researcher and we identify five …
Privacy-Preserving Cloud-Assisted Data Analytics,
2021
University of Arkansas, Fayetteville
Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao
Graduate Theses and Dissertations
Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.
Cloud computing has become more and more popular in …
Development Of A Reference Design For Intrusion Detection Using Neural Networks For A Smart Inverter,
2021
University of Arkansas, Fayetteville
Development Of A Reference Design For Intrusion Detection Using Neural Networks For A Smart Inverter, Ammar Mohammad Khan
Graduate Theses and Dissertations
The purpose of this thesis is to develop a reference design for a base level implementation of an intrusion detection module using artificial neural networks that is deployed onto an inverter and runs on live data for cybersecurity purposes, leveraging the latest deep learning algorithms and tools. Cybersecurity in the smart grid industry focuses on maintaining optimal standards of security in the system and a key component of this is being able to detect cyberattacks. Although researchers and engineers aim to design such devices with embedded security, attacks can and do still occur. The foundation for eventually mitigating these attacks …
