Digital Commons Network^™

A Hierarchical Temporal Memory Sequence Classifier For Streaming Data, Jeffrey Barnett

CCAC Theses and Dissertations

Real-world data streams often contain concept drift and noise. Additionally, it is often the case that due to their very nature, these real-world data streams also include temporal dependencies between data. Classifying data streams with one or more of these characteristics is exceptionally challenging. Classification of data within data streams is currently the primary focus of research efforts in many fields (i.e., intrusion detection, data mining, machine learning). Hierarchical Temporal Memory (HTM) is a type of sequence memory that exhibits some of the predictive and anomaly detection properties of the neocortex. HTM algorithms conduct training through exposure to a stream …

Adaptive Batch Size Selection In Active Learning For Regression, Anthony L. Faulds

CCAC Theses and Dissertations

Training supervised machine learning models requires labeled examples. A judicious choice of examples is helpful when there is a significant cost associated with assigning labels. This dissertation aims to improve upon a promising extant method - Batch-mode Expected Model Change Maximization (B-EMCM) method - for selecting examples to be labeled for regression problems. Specifically, it aims to develop and evaluate alternate strategies for adaptively selecting batch size in B-EMCM, named adaptive B-EMCM (AB-EMCM).

By determining the cumulative error that occurs from the estimation of the stochastic gradient descent, a stop criteria for each iteration of the batch can be specified …

Detecting And Protecting Against Ai-Synthesized Faces, Yuezun Li

Legacy Theses & Dissertations (2009 - 2024)

The recent advances in deep learning and the availability of vast volume of online personal images and videos have drastically improved the reality of synthesized faces in images and videos. While there are interesting and creative applications of the AI face synthesis systems, they can also be weaponized, as it can create the illusions of a person's presence and activities that do not occur in reality, which results in serious political, social, financial, and legal consequences. Therefore, it is of great importance to develop effective method to expose the AI-synthesized faces. In this thesis, a set of our recent efforts …

Using Ai To Analyze Patent Claim Indefiniteness, Dean Alderucci, Kevin Ashley

IP Theory

We describe how to use artificial intelligence (AI) techniques to partially automate a type of legal analysis, determining whether a patent claim satisfies the definiteness requirement. Although fully automating such a high-level cognitive task is well beyond state-of-the-art AI, we show that AI can nevertheless assist the decision maker in making this determination. Specifically, the use of custom AI technology can aid the decision maker by (1) mining patent text to rapidly bring relevant information to the decision maker’s attention, and (2) suggesting simple inferences that can be drawn from that information.

We begin by summarizing the law related to …

Ai Report: Humanity Is Doomed. Send Lawyers, Guns, And Money!, Ashley M. London

Law Faculty Publications

AI systems are powerful technologies being built and implemented by private corporations motivated by profit, not altruism. Change makers, such as attorneys and law students, must therefore be educated on the benefits, detriments, and pitfalls of the rapid spread, and often secret implementation of this technology. The implementation is secret because private corporations place proprietary AI systems inside of black boxes to conceal what is inside. If they did not, the popular myth that AI systems are unbiased machines crunching inherently objective data would be revealed as a falsehood. Algorithms created to run AI systems reflect the inherent human categorization …

Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …

Machine Learning? In My Election? It's More Likely Than You Think: Voting Rules Via Neural Networks, Daniel Firebanks-Quevedo

Honors Papers

Impossibility theorems in social choice have represented a barrier in the creation of universal, non-dictatorial, and non-manipulable voting rules, highlighting a key trade-off between social welfare and strategy-proofness. However, a social planner may be concerned with only a particular preference distribution and wonder whether it is possible to better optimize this trade-off. To address this problem, we propose an end-to-end, machine learning-based framework that creates voting rules according to a social planner's constraints, for any type of preference distribution. After experimenting with rank-based social choice rules, we find that automatically-designed rules are less susceptible to manipulation than most existing rules, …

Remark On Artificial Intelligence, Humanoid And Terminator Scenario: A Neutrosophic Way To Futurology, Victor Christianto, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This article is an update of our previous article in this SGJ journal, titled: On Gödel's Incompleteness Theorem, Artificial Intelligence & Human Mind [7]. We provide some commentary on the latest developments around AI, humanoid robotics, and future scenario. Basically, we argue that a more thoughtful approach to the future is "technorealism."

The Ghost In The Machine: Artificial Intelligence In Law Schools, Emily M. Janoski-Haehlen, Sarah Starnes

Akron Law Faculty Publications

This article addresses the different topics law schools are teaching and how each either succeeds or fails at teaching students to be technologically competent. This article provides a small guide to some of the proven-successful classes and technologies taught and how they can be incorporated into a law school's current curriculum. This article aims to assist in creating a bright line and uniform standard to assist all law schools in producing "tech-savvy" lawyers. A big part of being technologically competent is the ability to understand and utilize, not rely on, artificial intelligence. This article discusses the use of artificial intelligence …

Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily

All Works

© 2013 IEEE. Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the …

Ai And Machine Learning Usage In Actuarial Science, Joanna Riley

Williams Honors College, Honors Research Projects

Some people in the world work hard and do whatever it takes in order to get a job that they love. There are others that don’t care about their jobs and solely perform them in order to make money. So, there are individuals or groups that wouldn’t care if a machine or computer were to replace them in their job, but others would be devastated. The question for this paper is: Can actuaries be completely replaced by computers, or do we need the human mind in order to make proper decisions and judgements?

Key words and phrases: actuarial science, artificial …

An Automated Method For Detecting Water Levels Using Computer Vision And Artificial Intelligence, Priyanjani Chowdary Chandra

Graduate Research Theses & Dissertations

Flooding is one of the most dangerous weather events today. Between 2015-2019, on average, it has caused more than 130 deaths every year in the USA alone. World Health Organization has reported that, between 1998-2017, floods have affected more than 2 billion people worldwide. The devastating nature of flood necessitates the continuous monitoring of water level in the rivers and streams in flood-prone areas to detect the incoming flood. In this thesis, we have designed and implemented a computer vision and AI-based system that continuously detect the water level in the creek. Our solution employs an effective template matching algorithm …

Beneficial Precaution: A Proposed Approach To Uncertain Technological Dangers, Edward L. Rubin

Vanderbilt Journal of Entertainment & Technology Law

As a result of the specialization and cumulation of knowledge in the era of High Modernity, research and development in most technical fields is largely incomprehensible to anyone outside that field. What should policy makers do when technical specialists disagree, and particularly when some predict an oncoming catastrophe and others dismiss the concern? This is the situation with the so-called Singularity, the point at which machines design, build, and operate other machines. Some experts in cybernetics and artificial intelligence argue that this is imminent, while others consign the possibility to science fiction. If the skeptics are right, nothing need be …

Intelligent Cinematic Camera Control For Real-Time Graphics Applications, Ian Harris Meeder

Master's Theses

E-sports is currently estimated to be a billion dollar industry which is only growing in size from year to year. However the cinematography of spectated games leaves much to be desired. In most cases, the spectator either gets to control their own freely-moving camera or they get to see the view that a specific player sees. This thesis presents a system for the generation of cinematically-pleasing views for spectating real-time graphics applications. A custom real-time engine has been built to demonstrate the effect of this system on several different game modes with varying visual cinematic constraints, such as the rule …

Implementation Considerations For Mitigating Bias In Supervised Machine Learning, Bardia Bijani Aval

CSB and SJU Distinguished Thesis

Machine Learning (ML) is an important component of computer science and a mainstream way of making sense of large amounts of data. Although the technology is establishing new possibilities in different fields, there are also problems to consider, one of which is bias. Due to the inductive reasoning of ML algorithms in creating mathematical models, the predictions and trends found by the models will never necessarily be true – just more or less probable. Knowing this, it is unreasonable for us to expect the applied deductive reasoning of these models to ever be fully unbiased. Therefore, it is important that …

Using Ai And Machine Learning To Indicate Shale Anisotropy And Assist In Completions Design, Cole E. Palmer

Graduate Theses, Dissertations, and Problem Reports (ETD)

Operating companies in the unconventional Marcellus shale play have all faced a similar and problematic issue, while attempting to produce natural gas over the last decade. Companies have quickly realized that not every perforation along their horizontal wells are producing gas. In fact, producing perforations are only ranging from 15%-70% of the total perforations along the horizontal wellbore [1]. This unexplained issue results in millions of dollars in lost revenue per well, in addition to the sunk cost of paying for completions that are not actually yielding any produced gas.

What is causing these perforations to have no produced gas? …

Searching For Needles In The Cosmic Haystack, Thomas Ryan Devine

Graduate Theses, Dissertations, and Problem Reports (ETD)

Searching for pulsar signals in radio astronomy data sets is a difficult task. The data sets are extremely large, approaching the petabyte scale, and are growing larger as instruments become more advanced. Big Data brings with it big challenges. Processing the data to identify candidate pulsar signals is computationally expensive and must utilize parallelism to be scalable. Labeling benchmarks for supervised classification is costly. To compound the problem, pulsar signals are very rare, e.g., only 0.05% of the instances in one data set represent pulsars. Furthermore, there are many different approaches to candidate classification with no consensus on a best …

Artificial Intelligence-Based Models For The Qualitative And Quantitative Prediction Of Aphytochemical Compound Using Hplc Method, Abdullahi Garba Usman, Seli̇n Işik, Sani Isah Abba, Fi̇li̇z Meri̇çli̇

Turkish Journal of Chemistry

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile, Annona squamosal, Camellia sinensis (tea), and coriander (Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to …

Could A Robot Be Your Psychotherapist?, Benjamin Huston

Graduate School of Professional Psychology: Doctoral Papers and Masters Projects

As technology has advanced over the years, it has been integrated into psychotherapy and changed the way that people receive mental health care (Schopp, Demiris, & Glueckauf, 2006). Many of these advances, such as telehealth practices, were seen as unsustainable until the public Internet offered broader access to technology-based care in the 1990s (Schopp, Demiris, & Glueckauf, 2006). These technology-based practices have since grown in popularity and with a recent increase in telehealth practices, text-based therapies, and applications to aid in mental health practices, modern therapy looks very different than it did even ten years ago (Fiske, Henningsen, & Buyx, …

Can Algorithms Promote Fair Use?, Peter K. Yu

FIU Law Review

No abstract provided.

Empowering Qualitative Research Methods In Education With Artificial Intelligence, Luca Longo

Conference papers

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches …

Diota: Decentralized Ledger Based Framework For Data Authenticity Protection In Iot Systems, Lei Xu, Lin Chen, Zhimin Gao, Xinxin Fan, Taeweon Suh, Weidong Shi

Computer Science Faculty Publications

It is predicted that more than 20 billion IoT devices will be deployed worldwide by 2020. These devices form the critical infrastructure to support a variety of important applications such as smart city, smart grid, and industrial internet. To guarantee that these applications work properly, it is imperative to authenticate these devices and data generated from them. Although digital signatures can be applied for these purposes, the scale of the overall system and the limited computation capability of IoT devices pose two big challenges. In order to overcome these obstacles, we propose DIoTA, a novel decentralized ledger-based authentication framework for …

Introduction: Intelligent Entertainment: Shaping Policies On The Algorithmic Generation And Regulation Of Creative Works, Hannibal Travis

FIU Law Review

No abstract provided.

A Holistic Review Of Cybersecurity And Reliability Perspectives In Smart Airports, Nickolaos Koroniotis, Nour Moustafa, Francesco Schiliro, Praveen Gauravaram, Helge Janicke

Research outputs 2014 to 2021

Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence of smart airports. Services and systems powered by the IoT enable smart airports to have enhanced robustness, efficiency and control, governed by real-time monitoring and analytics. Smart sensors control the environmental conditions inside the airport, automate passenger-related actions and support airport security. However, these augmentations and automation introduce security threats to network systems of smart airports. Cyber-attackers demonstrated the susceptibility of IoT systems and networks to Advanced Persistent Threats (APT), due to hardware constraints, software flaws or IoT misconfigurations. With the increasing complexity of attacks, …

Augmenting Education: Ethical Considerations For Incorporating Artificial Intelligence In Education, Dana Remian

Instructional Design Capstones Collection

Artificial intelligence (AI) has existed in theory and practice for decades, but applications have been relatively limited in most domains. Recent developments in AI and computing have placed AI-enhanced applications in various industries and a growing number of consumer products. AI platforms and services aimed at enhancing educational outcomes and taking over administrative tasks are becoming more prevalent and appearing in more and more classrooms and offices. Conversations about the disruption and ethical concerns created by AI are occurring in many fields. The development of the technology threatens to outpace academic discussion of its utility and pitfalls in education, however. …

“Where’S The I-O?” Artificial Intelligence And Machine Learning In Talent Management Systems, Manuel F. Gonzalez, John F. Capman, Frederick L. Oswald, Evan R. Theys, David L. Tomczak

Personnel Assessment and Decisions

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; …

What Do You Mean? Research In The Age Of Machines, Arthur J. Boston

Faculty & Staff Research and Creative Activity

What Do You Mean?” was an undeniable bop of its era in which Justin Bieber explores the ambiguities of romantic communication. (I pinky promise this will soon make sense for scholarly communication librarians interested in artificial intelligence [AI].) When the single hit airwaves in 2015, there was a meta-debate over what Bieber meant to add to public discourse with lyrics like “What do you mean? Oh, oh, when you nod your head yes, but you wanna say no.” It is unlikely Bieber had consent culture in mind, but the failure of his songwriting team to take into account that some …

Artificial Intelligence In Higher Education, Hamis Juma

Master of Education

This study adopted an action research methodology to explore how Artificial Intelligence enhances learning in higher education. AI is the technology that makes the ICT devices to solve cognitive tasks as a human would have done by using realtime data. Such a giant leap in digital technologies has changed the way people learn. In the study, baseline data showed there is a potential of using Artificial Intelligence in teaching and learning, henceforth, an intervention with Artificial Intelligence tool Grammarly was introduced in the class. During the intervention in this study, Grammarly was used in the teaching and learning and later …

Experiencing Voice-Activated Artificial Intelligence Assistants In The Home: A Phenomenological Approach, Valerie K. Jones

College of Education and Human Sciences: Dissertations, Theses, and Student Research

Voice-controlled artificial intelligence (AI) assistants, such as Amazon’s Alexa or Google’s Assistant, serve as the gateway to the Internet of Things and connected home, executing the commands of its users, providing information, entertainment, utility, and convenience while enabling consumers to bypass the advertising they would typically see on a screen. This “screen-less” communication presents significant challenges for brands used to “pushing” messages to audiences in exchange for the content they seek. It also raises questions about data collection, usage, and privacy. Brands need to understand how and why audiences engage with AI assistants, as well as the risks with these …

Realtime Object Detection Via Deep Learning-Based Pipelines, James G. Shanahan, Liang Dai

Information Systems and Analytics Department Faculty Conference Proceedings

Ever wonder how the Tesla Autopilot system works (or why it fails)? In this tutorial we will look under the hood of self-driving cars and of other applications of computer vision and review state-of-the-art tech pipelines for object detection such as two-stage approaches (e.g., Faster R-CNN) or single-stage approaches (e.g., YOLO/SSD). This is accomplished via a series of Jupyter Notebooks that use Python, OpenCV, Keras, and Tensorflow. No prior knowledge of computer vision is assumed (although it will be help!). To this end we begin this tutorial with a review of computer vision and traditional approaches to object detection such …