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Articles 1 - 19 of 19
Full-Text Articles in Engineering
Lung Nodules Identification In Ct Scans Using Multiple Instance Learning., Wiem Safta
Lung Nodules Identification In Ct Scans Using Multiple Instance Learning., Wiem Safta
Electronic Theses and Dissertations
Computer Aided Diagnosis (CAD) systems for lung nodules diagnosis aim to classify nodules into benign or malignant based on images obtained from diverse imaging modalities such as Computer Tomography (CT). Automated CAD systems are important in medical domain applications as they assist radiologists in the time-consuming and labor-intensive diagnosis process. However, most available methods require a large collection of nodules that are segmented and annotated by radiologists. This process is labor-intensive and hard to scale to very large datasets. More recently, some CAD systems that are based on deep learning have emerged. These algorithms do not require the nodules to …
Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar
Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar
Electronic Theses and Dissertations
The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for …
Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy
Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy
Faculty Scholarship
As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. This framework is designed to direct attention to pertinent system properties without requiring unwieldy amounts of accuracy. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of …
Impossibility Results In Ai: A Survey, Mario Brcic, Roman Yampolskiy
Impossibility Results In Ai: A Survey, Mario Brcic, Roman Yampolskiy
Faculty Scholarship
An impossibility theorem demonstrates that a particular problem or set of problems cannot be solved as described in the claim. Such theorems put limits on what is possible to do concerning artificial intelligence, especially the super-intelligent one. As such, these results serve as guidelines, reminders, and warnings to AI safety, AI policy, and governance researchers. These might enable solutions to some long-standing questions in the form of formalizing theories in the framework of constraint satisfaction without committing to one option. In this paper, we have categorized impossibility theorems applicable to the domain of AI into five categories: deduction, indistinguishability, induction, …
Death In Genetic Algorithms, Micah Burkhardt, Roman Yampolskiy
Death In Genetic Algorithms, Micah Burkhardt, Roman Yampolskiy
Faculty Scholarship
Death has long been overlooked in evolutionary algorithms. Recent research has shown that death (when applied properly) can benefit the overall fitness of a population and can outperform sub-sections of a population that are “immortal” when allowed to evolve together in an environment [1]. In this paper, we strive to experimentally determine whether death is an adapted trait and whether this adaptation can be used to enhance our implementations of conventional genetic algorithms. Using some of the most widely accepted evolutionary death and aging theories, we observed that senescent death (in various forms) can lower the total run-time of genetic …
Passive Method For 3d Reconstruction Of Human Jaw: Theory And Application., Mohamad Ghanoum
Passive Method For 3d Reconstruction Of Human Jaw: Theory And Application., Mohamad Ghanoum
Electronic Theses and Dissertations
Oral dental applications based on visual data pose various challenges. There are problems with lighting (effect of saliva, tooth dis-colorization, gum texture, and other sources of specularity) and motion (even inevitable slight motions of the upper/ lower jaw may lead to errors far beyond the desired tolerance of sub-millimeter accuracy). Nowadays, the dental CAM systems have become more compromised and accurate to obtain the geometric data of the jaw from the active sensor (laser scanner). However, they have not met the expectations and the needs of dental professionals in many ways. The probes in these systems are bulky { even …
Multilateration Index., Chip Lynch
Multilateration Index., Chip Lynch
Electronic Theses and Dissertations
We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …
Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese
Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese
Electronic Theses and Dissertations
Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …
Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi
Cosine-Based Explainable Matrix Factorization For Collaborative Filtering Recommendation., Pegah Sagheb Haghighi
Electronic Theses and Dissertations
Recent years saw an explosive growth in the amount of digital information and the number of users who interact with this information through various platforms, ranging from web services to mobile applications and smart devices. This increase in information and users has naturally led to information overload which inherently limits the capacity of users to discover and find their needs among the staggering array of options available at any given time, the majority of which they may never become aware of. Online services have handled this information overload by using algorithmic filtering tools that can suggest relevant and personalized information …
Motion And Emotion Estimation For Robotic Autism Intervention., Jacob M Berdichevsky
Motion And Emotion Estimation For Robotic Autism Intervention., Jacob M Berdichevsky
Electronic Theses and Dissertations
Robots have recently emerged as a novel approach to treating autism spectrum disorder (ASD). A robot can be programmed to interact with children with ASD in order to reinforce positive social skills in a non-threatening environment. In prior work, robots were employed in interaction sessions with ASD children, but their sensory and learning abilities were limited, while a human therapist was heavily involved in “puppeteering” the robot. The objective of this work is to create the next-generation autism robot that includes several new interactive and decision-making capabilities that are not found in prior technology. Two of the main features that …
Linking Social Media, Medical Literature, And Clinical Notes Using Deep Learning., Mohsen Asghari
Linking Social Media, Medical Literature, And Clinical Notes Using Deep Learning., Mohsen Asghari
Electronic Theses and Dissertations
Researchers analyze data, information, and knowledge through many sources, formats, and methods. The dominant data format includes text and images. In the healthcare industry, professionals generate a large quantity of unstructured data. The complexity of this data and the lack of computational power causes delays in analysis. However, with emerging deep learning algorithms and access to computational powers such as graphics processing unit (GPU) and tensor processing units (TPUs), processing text and images is becoming more accessible. Deep learning algorithms achieve remarkable results in natural language processing (NLP) and computer vision. In this study, we focus on NLP in the …
Flight Trajectory Prediction For Aeronautical Communications., Nathan T Schimpf
Flight Trajectory Prediction For Aeronautical Communications., Nathan T Schimpf
Electronic Theses and Dissertations
The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing a limited spectrum among aircraft and ground systems. Emerging approaches to this spectrum allocation task mostly consider machine learning techniques reliant on aircraft and Air Traffic Control (ATC) sector data. Much of this data, however, is not directly available. This thesis considers the development of two such data products: the 4D trajectory (latitude, longitude, altitude, and time) of aircraft, and the anticipated airspace utilization and communication demand within an ATC sector. Data predictions are treated as a time …
Designing Ai For Explainability And Verifiability: A Value Sensitive Design Approach To Avoid Artificial Stupidity In Autonomous Vehicles, Steven Umbrello, Roman V. Yampolskiy
Designing Ai For Explainability And Verifiability: A Value Sensitive Design Approach To Avoid Artificial Stupidity In Autonomous Vehicles, Steven Umbrello, Roman V. Yampolskiy
Faculty Scholarship
One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents. This paper explores how decision matrix algorithms, via the belief-desire-intention model for autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for …
Computational Frameworks For Microrna Functional Analysis Of Inter-Kingdom And Indirect Targeting., Mohammed Sayed
Computational Frameworks For Microrna Functional Analysis Of Inter-Kingdom And Indirect Targeting., Mohammed Sayed
Electronic Theses and Dissertations
Genes are DNA sequences that encode the information needed to synthesize molecules necessary for the function of the cell. Some genes are called protein-coding genes because they have the code required to manufacture proteins. The expression of a certain gene means its product (protein) is produced. Although some genes are not protein-coding, they regulate the gene expression of other protein-coding genes. Of these, microRNAs (miRNAs) are small RNA molecules that inhibit the expression of other genes by binding to their mRNA transcripts. miRNAs have been shown to be linked to several biological processes like development and diseases like cancer. Recently, …
Multi-Style Explainable Matrix Factorization Techniques For Recommender Systems., Olurotimi Nugbepo Seton
Multi-Style Explainable Matrix Factorization Techniques For Recommender Systems., Olurotimi Nugbepo Seton
Electronic Theses and Dissertations
Black-box recommender system models are machine learning models that generate personalized recommendations without explaining how the recommendations were generated to the user or giving them a way to correct wrong assumptions made about them by the model. However, compared to white-box models, which are transparent and scrutable, black-box models are generally more accurate. Recent research has shown that accuracy alone is not sufficient for user satisfaction. One such black-box model is Matrix Factorization, a State of the Art recommendation technique that is widely used due to its ability to deal with sparse data sets and to produce accurate recommendations. Recent …
Machine Learning Approaches For Lung Cancer Diagnosis., Ahmed Mahmoud Ahmed Shaffie
Machine Learning Approaches For Lung Cancer Diagnosis., Ahmed Mahmoud Ahmed Shaffie
Electronic Theses and Dissertations
The enormity of changes and development in the field of medical imaging technology is hard to fathom, as it does not just represent the technique and process of constructing visual representations of the body from inside for medical analysis and to reveal the internal structure of different organs under the skin, but also it provides a noninvasive way for diagnosis of various disease and suggest an efficient ways to treat them. While data surrounding all of our lives are stored and collected to be ready for analysis by data scientists, medical images are considered a rich source that could provide …
Restaurant Style Prediction Using Word2vec And Support Vector Machine., Saleh Abdullah Almohaimeed
Restaurant Style Prediction Using Word2vec And Support Vector Machine., Saleh Abdullah Almohaimeed
Electronic Theses and Dissertations
Natural Language Processing represents a quantum leap for governance and industries. It enables them to have an insight into hidden patterns and information within their data. In this thesis, we have worked on an important field in Natural Language Processing, which is Text Classification. Our goal is to help restaurant owners to find which dishes customers like more. To do that we have used a dataset from Yelp.com that has 150,000 restaurant reviews, then count the most frequent dishes mentioned. However, this way is not effective except if these reviews are categorized into different restaurants-styles. For this reason, we have …
Understanding And Avoiding Ai Failures: A Practical Guide., Robert Max C Williams
Understanding And Avoiding Ai Failures: A Practical Guide., Robert Max C Williams
Electronic Theses and Dissertations
As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of seeking a root cause of accidents, we identify where attention should be paid to safety for current …
Transdisciplinary Ai Observatory—Retrospective Analyses And Future-Oriented Contradistinctions, Nadisha Marie Aliman, Leon Kester, Roman Yampolskiy
Transdisciplinary Ai Observatory—Retrospective Analyses And Future-Oriented Contradistinctions, Nadisha Marie Aliman, Leon Kester, Roman Yampolskiy
Faculty Scholarship
In the last years, artificial intelligence (AI) safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently transdisciplinary AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing concrete practical examples. Distinguishing between unintentionally and intentionally triggered AI risks with diverse socio-psycho-technological impacts, we exemplify a retrospective descriptive analysis followed by a retrospective counterfactual risk analysis. Building on …