Opening Social,
2022
University of Nebraska at Omaha
Unreasonable: A Strict Liability Solution To The Ftc’S Data Security Problem,
2022
Antonin Scalia Law School
Unreasonable: A Strict Liability Solution To The Ftc’S Data Security Problem, James C. Cooper, Bruce H. Kobayashi
Michigan Technology Law Review
For over two decades, the FTC creatively employed its capacious statute to police against shoddy data practices. Although the FTC’s actions were arguably needed at the time to fill a gap in enforcement, there are reasons to believe that its current approach has outlived its usefulness and is in serious need of updating. In particular, our analysis shows that the FTC’s current approach to data security is unlikely to instill anything close to optimal incentives for data holders. These shortcomings cannot be fixed through changes to the FTC enforcement approach, as they are largely generated by a mismatch between the …
A False Sense Of Security - Organizations Need A Paradigm Shift On Protecting Themselves Against Apts,
2022
Dakota State University
A False Sense Of Security - Organizations Need A Paradigm Shift On Protecting Themselves Against Apts, Srinivasulu R. Vuggumudi
Masters Theses & Doctoral Dissertations
Organizations Advanced persistent threats (APTs) are the most complex cyberattacks and are generally executed by cyber attackers linked to nation-states. The motivation behind APT attacks is political intelligence and cyber espionage. Despite all the awareness, technological advancements, and massive investment, the fight against APTs is a losing battle for organizations. An organization may implement a security strategy to prevent APTs. However, the benefits to the security posture might be negligible if the measurement of the strategy’s effectiveness is not part of the plan. A false sense of security exists when the focus is on implementing a security strategy but not …
Leaderboard Design Principles Influencing User Engagement In An Online Discussion,
2022
Dakota State University
Leaderboard Design Principles Influencing User Engagement In An Online Discussion, Brian S. Bovee
Masters Theses & Doctoral Dissertations
Along with the popularity of gamification, there has been increased interest in using leaderboards to promote engagement with online learning systems. The existing literature suggests that when leaderboards are designed well they have the potential to improve learning, but qualitative investigations are required in order to reveal design principles that will improve engagement. In order to address this gap, this qualitative study aims to explore students' overall perceptions of popular leaderboard designs in a gamified, online discussion. Using two leaderboards reflecting performance in an online discussion, this study evaluated multiple leaderboard designs from student interviews and other data sources regarding …
Industrial Digital Twins At The Nexus Of Nextg Wireless Networks And Computational Intelligence: A Survey,
2022
National University of Sciences and Technology, Pakistan
Industrial Digital Twins At The Nexus Of Nextg Wireless Networks And Computational Intelligence: A Survey, Shah Zeb, Aamir Mahmood, Syed Ali Hassan, Md. Jalil Piran, Mikael Gidlund, Mohsen Guizani
Machine Learning Faculty Publications
By amalgamating recent communication and control technologies, computing and data analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber–physical worlds through cyber–physical systems (CPS) and digital twin (DT) for monitoring, optimization, and prognostics of industrial processes. A DT enables interaction with the digital image of the industrial physical objects/processes to simulate, analyze, and control their real-time operation. DT is rapidly diffusing in numerous industries with the interdisciplinary advances in the industrial Internet of things (IIoT), edge and cloud computing, machine learning, artificial intelligence, and advanced data analytics. However, the existing literature lacks in identifying and discussing the role and …
A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics,
2022
Old Dominion University
A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides
College of Sciences Posters
With the evolution in detector technologies and electronic components used in the Nuclear Physics field, experimental setups become larger and more complex. Faster electronics enable particle accelerator experiments to run with higher beam intensity, providing more interactions per time and more particles per interaction. However, the increased beam intensities present a challenge to particle detectors because of the higher amount of noise and uncorrelated signals. Higher noise levels lead to a more challenging particle reconstruction process by increasing the number of combinatorics to analyze and background signals to eliminate. On the other hand, increasing the beam intensity can provide physics …
Convolutional Neural Network For Covid-19 Detection In Chest X-Rays,
2022
University of South Dakota
Convolutional Neural Network For Covid-19 Detection In Chest X-Rays, Joshua Elliot Henderson
Honors Thesis
The COVID-19 pandemic has had a large effect on almost every facet of life. As COVID-19 was a disease only discovered in recent history, there is comparatively little data on the disease, how we detect it, and how we cure it. Deep learning is a powerful tool that can be used to learn to classify information in ways that humans might not be able to. This allows computers to learn on relatively little data and provide exceptional results. In this paper, I propose a novel convolutional neural network (CNN) for the detection of COVID-19 from chest X-rays called basicConv. This …
Visual Homing For Robot Teams: Do You See What I See?,
2022
Fordham University
Visual Homing For Robot Teams: Do You See What I See?, Damian Lyons, Noah Petzinger
Faculty Publications
Visual homing is a lightweight approach to visual navigation which does not require GPS. It is very attractive for robot platforms with a low computational capacity. However, a limitation is that the stored home location must be initially within the field of view of the robot. Motivated by the increasing ubiquity of camera information we propose to address this line-of-sight limitation by leveraging camera information from other robots and fixed cameras. To home to a location that is not initially within view, a robot must be able to identify a common visual landmark with another robot that can be used …
The Illusion Of Agency In Human–Computer Interaction,
2022
University of the Pacific
The Illusion Of Agency In Human–Computer Interaction, Michael Madary
College of the Pacific Faculty Articles
This article makes the case that our digital devices create illusions of agency. There are times when users feel as if they are in control when in fact they are merely responding to stimuli on the screen in predictable ways. After the introduction, the second section of the article offers examples of illusions of agency that do not involve human–computer interaction in order to show that such illusions are possible and not terribly uncommon. The third and fourth sections of the article cover relevant work from empirical psychology, including the cues that are known to generate the sense of agency. …
Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion,
2022
Louisiana State University
Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines
Honors Theses
No abstract provided.
Lyapunov-Based Economic Model Predictive Control For Detecting And Handling Actuator And Simultaneous Sensor/Actuator Cyberattacks On Process Control Systems,
2022
Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI
Lyapunov-Based Economic Model Predictive Control For Detecting And Handling Actuator And Simultaneous Sensor/Actuator Cyberattacks On Process Control Systems, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
The controllers for a cyber-physical system may be impacted by sensor measurement cyberattacks, actuator signal cyberattacks, or both types of attacks. Prior work in our group has developed a theory for handling cyberattacks on process sensors. However, sensor and actuator cyberattacks have a different character from one another. Specifically, sensor measurement attacks prevent proper inputs from being applied to the process by manipulating the measurements that the controller receives, so that the control law plays a role in the impact of a given sensor measurement cyberattack on a process. In contrast, actuator signal attacks prevent proper inputs from being applied …
Why Rectified Linear Unit Is Efficient In Machine Learning: One More Explanation,
2022
DigiPen Institute of Technology
Why Rectified Linear Unit Is Efficient In Machine Learning: One More Explanation, Barnabas Bede, Vladik Kreinovich, Uyen Pham
Departmental Technical Reports (CS)
In many applications, in particular, in econometric application, deep learning techniques are very effective. In this paper, we provide a new explanation for why rectified linear units -- the main units of deep learning -- are so effective. This explanation is similar to the usual explanation of why Gaussian (normal) distributions are ubiquitous -- namely, it is based on an appropriate limit theorem.
Game-Theoretic Approach Explains -- On The Qualitative Level -- The Antigenic Map Of Covid-19 Variants,
2022
The University of Texas at El Paso
Game-Theoretic Approach Explains -- On The Qualitative Level -- The Antigenic Map Of Covid-19 Variants, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong
Departmental Technical Reports (CS)
To effectively defend the population against future variants of Covid-19, it is important to be able to predict how it will evolve. For this purpose, it is necessary to understand the logic behind its evolution so far. At first glance, this evolution looks random and thus, difficult to predict. However, we show that already a simple game-theoretic model can actually explain -- on the qualitative level -- how this virus mutated so far.
When Is Deep Learning Better And When Is Shallow Learning Better: Qualitative Analysis,
2022
The University of Texas at El Paso
When Is Deep Learning Better And When Is Shallow Learning Better: Qualitative Analysis, Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich
Departmental Technical Reports (CS)
In many practical situations, deep neural networks work better than the traditional "shallow" ones, however, in some cases, the shallow neural networks lead to better results. At present, deciding which type of neural networks will work better is mostly done by trial and error. It is therefore desirable to come up with some criterion of when deep learning is better and when shallow is better. In this paper, we argue that this depends on whether the corresponding situation has natural symmetries: if it does, we expect deep learning to work better, otherwise we expect shallow learning to be more effective. …
Why Constraint Interval Arithmetic Works Well: A Theorem Explains Empirical Success,
2022
DigiPen Institute of Technology
Why Constraint Interval Arithmetic Works Well: A Theorem Explains Empirical Success, Barnabas Bede, Marina Tuyako Mizukoshi, Weldon Lodwick, Martine Ceberio, Vladik Kreinovich
Departmental Technical Reports (CS)
Often, we are interested in a quantity that is difficult or impossible to measure directly, e.g., tomorrow's temperature. To estimate this quantity, we measure auxiliary easier-to-measure quantities that are related to the desired ones by a known dependence, and use the known relation to estimate the desired quantity. Measurements are never absolutely accurate, there is always a measurement error, i.e., a non-zero difference between the measurement result and the actual (unknown) value of the corresponding quantity. In many practical situations, the only information that we have about each measurement error is the bound on its absolute value. In such situations, …
Gamerz,
2022
San Jose State University
Gamerz, Derek Kwok
ART 108: Introduction to Games Studies
Gaming - it is a hobby enjoyed by many and easily accessible for all. But what is considered gaming? A game can be classified as something to do for past time or as an amusement. As it is defined in the oxford dictionary “gaming” can be categorized into two definitions: 1.the playing of games developed to teach something or to help solve a problem, as in a military or business situation, or 2. Digital Technology. the playing of computer or video games. According to the definition on Dictionary.com, board games or physical games can still be considered gaming. Definition two …
The Social Problems And Benefits Of Video Games,
2022
San Jose State University
The Social Problems And Benefits Of Video Games, Steven Ly
ART 108: Introduction to Games Studies
In today’s society, video games have improved and increased alongside technology. Many games have made many communities increase their social media intake and gaming addiction. In the uprise of video games, multiple genres of video games have been created to contain the gamer. This paper will discuss the number of negatives and positives that affect a video gamer. We will also discuss other factors that could correlate to games involving people. The downsides and upsides of video gaming will primarily revolve around social problems that gamers develop and or positive outcomes from gaming. We will dive into the topics such …
Psychological Effects Of Video Games,
2022
San Jose State University
Psychological Effects Of Video Games, Myles Johnson
ART 108: Introduction to Games Studies
Through the birth of the computer, our world has seen a rapid advancement in the multi-faceted use of this technology. The advancements in computers brought about the invention of video game consoles. Basically a different type of computer. Game consoles today are all basically computers, they contain a hard drive and operating system just like a computer (Daniel, 2012). Without even looking into the harmful effects of what a regular computer has on the brain and eyes of a person, one can assume that it is not beneficial to spend hours on one every day or even every other day. …
Super-High Resolution Imaging Using Easy Accessible Resources,
2022
Loyola Marymount University
Super-High Resolution Imaging Using Easy Accessible Resources, Jamison Murphy
LMU/LLS Theses and Dissertations
Most generic systems and hardware for non-governmental users lack capability to process images in high resolution coming from aerial crafts such as satellites, drones, airplanes and helicopters. These images are being displayed in poor quality due to the software running on low budgets, which restricts the high resolution they need. In this project I researched ways to obtain super high resolution images from aerial crafts for low cost and compared which method works best in producing the clearest and fastest images. I connected with the Loyola Marymount University Marketing team to collaborate with their photographers in producing the best quality …
Unsupervised Automatic Speech Recognition: A Review,
2022
United Arab Emirates University & Mohamed bin Zayed University of Artificial Intelligence
Unsupervised Automatic Speech Recognition: A Review, Hanan Aldarmaki, Asad Ullah, Sreepratha Ram, Nazar Zaki
Natural Language Processing Faculty Publications
Automatic Speech Recognition (ASR) systems can be trained to achieve remarkable performance given large amounts of manually transcribed speech, but large labeled data sets can be difficult or expensive to acquire for all languages of interest. In this paper, we review the research literature to identify models and ideas that could lead to fully unsupervised ASR, including unsupervised sub-word and word modeling, unsupervised segmentation of the speech signal, and unsupervised mapping from speech segments to text. The objective of the study is to identify the limitations of what can be learned from speech data alone and to understand the minimum …
