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Artificial Intelligence

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Articles 121 - 148 of 148

Full-Text Articles in Computer Engineering

Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth Jan 2020

Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth

Publications

During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …

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Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola Jan 2020

Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola

Articles

This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …

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Voice Controlled Augmented Reality: A Comparison Of Speech-Recognition Tools For Ar Applications, Juan Estrella Dec 2019

Voice Controlled Augmented Reality: A Comparison Of Speech-Recognition Tools For Ar Applications, Juan Estrella

Publications and Research

Augmented Reality (AR) refers to the technologies that enhance the version of the physical environment with computer-generated sensory input such as sound and graphics overlaid on top of the user’s view of the real world. Artificial Intelligence (AI) studies how to make computer programs and machines "smart" and take decisions. Our research project focuses on exploring the Integration of AI in AR applications. Specifically, on using Speech Recognition or Natural Language Processing for controlling virtual AR objects and enhancing the human-computer interaction. It is obvious that integration of AI and AR is of great value. However, for developers, it is …

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Artificial Intelligence Empowered Uavs Data Offloading In Mobile Edge Computing, Nicholas Alexander Kemp Nov 2019

Artificial Intelligence Empowered Uavs Data Offloading In Mobile Edge Computing, Nicholas Alexander Kemp

Electrical and Computer Engineering ETDs

The advances introduced by Unmanned Aerial Vehicles (UAVs) are manifold and have paved the path for the full integration of UAVs, as intelligent objects, into the Internet of Things (IoT). This paper brings artificial intelligence into the UAVs data offloading process in a multi-server Mobile Edge Computing (MEC) environment, by adopting principles and concepts from game theory and reinforcement learning. Initially, the autonomous MEC server selection for partial data offloading is performed by the UAVs, based on the theory of the stochastic learning automata. A non-cooperative game among the UAVs is then formulated to determine the UAVs' data to be …

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On The Potential, Feasibility, And Effectiveness Of Chat Bots In Public Health Research Going Forward, Stanley Mierzwa, Samir Souidi, Tammy Allen Sep 2019

On The Potential, Feasibility, And Effectiveness Of Chat Bots In Public Health Research Going Forward, Stanley Mierzwa, Samir Souidi, Tammy Allen

Center for Cybersecurity

This paper will discuss whether bots, particularly chat bots, can be useful in public health research and health or pharmacy systems operations. Bots have been discussed for many years; particularly when coupled with artificial intelligence, they offer the opportunity of automating mundane or error-ridden processes and tasks by replacing human involvement. This paper will discuss areas where there are greater advances in the use of bots, as well as areas that may benefit from the use of bots, and will offer practical ways to get started with bot technology. Several popular bot applications and bot development tools along with practical …

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An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari Aug 2019

An Explainable Recommender System Based On Semantically-Aware Matrix Factorization., Mohammed Sanad Alshammari

Electronic Theses and Dissertations

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less …

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Computer Vision Machine Learning And Future-Oriented Ethics, Abagayle Lee Blank Jun 2019

Computer Vision Machine Learning And Future-Oriented Ethics, Abagayle Lee Blank

Honors Projects

Computer Vision Machine Learning (CVML) in the application of facial recognition is currently being researched, developed, and deployed across the world. It is of interest to governments, technology companies, and consumers. However, fundamental issues remain related to human rights, error rates, and bias. These issues have the potential to create societal backlash towards the technology which could limit its benefits as well as harm people in the process. To develop facial recognition technology that will be beneficial to society in and beyond the next decade, society must put ethics at the forefront. Drawing on AI4People’s adaption of bioethics for AI, …

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On Using Ai Bots For Voice Controlled Augmented Reality Applications, Juan Estrella Apr 2019

On Using Ai Bots For Voice Controlled Augmented Reality Applications, Juan Estrella

Publications and Research

Artificial Intelligence (AI) has the potential to benefit society in the realms of medicine, security, manufacturing, entertainment, marketing, and many others. One of the advances of AI is in the field of Natural Language Processing and Speech Recognition; making computers understand what humans say and mean. On the other hand, the term Augmented Reality (AR) refers to the technologies that superimpose digital content generated by computers over the user’s view of the real world. AR technologies enhance the version of the physical environment with computergenerated sensory input such as sound, video, or graphics overlaid on top of the real-world view. …

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Intelligent Technology Of Command And Control System In The Rts Perspective, Wenfeng Wu, Zhang Yu, Rong Ming Jan 2019

Intelligent Technology Of Command And Control System In The Rts Perspective, Wenfeng Wu, Zhang Yu, Rong Ming

Journal of System Simulation

Abstract: Real-Time Strategy (RTS) games have important reference value for studying the intelligent technology of command and control systems. The similarities between RTS games and the strategic battle level command and control systems are described according to the decision process. The challenges brought by the problems of planning, learning, uncertainty and space-time reasoning in the intelligent technology of RTS games are analyzed. The key technologies and latest research progress of action sequence planning, plan recognition, state assessment, multi-agent collaboration and multi-scale AI are studied. The trend of intelligent technology development of strategic and operational level command and control systems is …

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Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat Jan 2019

Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat

Browse all Theses and Dissertations

Information Extraction (IE) techniques are developed to extract entities, relationships, and other detailed information from unstructured text. The majority of the methods in the literature focus on designing supervised machine learning techniques, which are not very practical due to the high cost of obtaining annotations and the difficulty in creating high quality (in terms of reliability and coverage) gold standard. Therefore, semi-supervised and distantly-supervised techniques are getting more traction lately to overcome some of the challenges, such as bootstrapping the learning quickly. This dissertation focuses on information extraction, and in particular entities, i.e., Named Entity Recognition (NER), from multiple domains, …

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Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee Jan 2019

Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee

Legacy Theses & Dissertations (2009 - 2024)

Deep Learning is the new state-of-the-art technology in Image Processing. We applied Deep Learning techniques for identification of diseases from Radiographs made publicly available by NIH. We applied some Feature Engineering approach to augment the data from Anterior-Posterior position to Posterior-Anterior position and vice-versa for all the diseases, at the same point we suppressed ‘No Finding’ radiographs which contributed to more than 50% (approximately 60,000) of the dataset to top 1000 images. We also prepared a model by adding a huge amount of noise to the augmented data, which if need be can be deployed at rural locations which lack …

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Artificial Intelligence In The Assessment Of Transmission And Distribution Systems Under Natural Disasters Using Machine Learning And Deep Learning Techniques In A Knowledge Discovery Framework, Rossana Villegas Jan 2019

Artificial Intelligence In The Assessment Of Transmission And Distribution Systems Under Natural Disasters Using Machine Learning And Deep Learning Techniques In A Knowledge Discovery Framework, Rossana Villegas

Open Access Theses & Dissertations

Warming trends and increasing temperatures have been observed and reported by federal agencies, such as the National Oceanic and Atmospheric Administration (NOAA). Extreme-weather events, especially hurricanes, tornadoes and winter storms, are among the highly devastating natural disasters responsible for massive and prolonged power outages in Electrical Transmission and Distribution Systems (ETDS). Moreover, the failure rate probability of any system component under extreme-weather tends to increase in the impacted geographic area. This Dissertation proposes an Artificial Intelligence (AI) Decision Support System that can predict damage in the ETDS and allow operators to mitigate disastrous extreme weather events. The document reports the …

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Exploring Cyber-Physical Systems, Misbah Uddin Mohammed Jan 2019

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …

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A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne Jan 2018

A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne

Browse all Theses and Dissertations

Pictographs, commonly referred to as `emoji’, have become a popular way to enhance electronic communications. They are an important component of the language used in social media. With their introduction in the late 1990’s, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. In 2015, Instagram reported that nearly half of the photo comments posted on Instagram contain emoji, and in the same year, Twitter reported that the `face with tears of joy’ emoji has been tweeted 6.6 …

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Slither.Io Deep Learning Bot, James Caudill Jun 2017

Slither.Io Deep Learning Bot, James Caudill

Computer Engineering

Recent advances in deep learning and computer vision techniques and algorithms have inspired me to create a model application. The game environment used is Slither.io. The system has no previous understanding of the game and is able to learn its surroundings through feature detection and deep learning. Contrary to other agents, my bot is able to dynamically learn and react to its environment. It operates extremely well in early game, with little enemy encounters. It has difficulty transitioning to middle and late game due to limited training time. I will continue to develop this algorithm.

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Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney Jun 2017

Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney

Computer Science and Software Engineering

Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.

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Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna Jan 2017

Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna

Browse all Theses and Dissertations

The processing of structured and semi-structured content on the Web has been gaining attention with the rapid progress in the Linking Open Data project and the development of commercial knowledge graphs. Knowledge graphs capture domain-specific or encyclopedic knowledge in the form of a data layer and add rich and explicit semantics on top of the data layer to infer additional knowledge. The data layer of a knowledge graph represents entities and their descriptions. The semantic layer on top of the data layer is called the schema (ontology), where relationships of the entity descriptions, their classes, and the hierarchy of the …

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Scale Up Bayesian Network Learning, Xiannian Fan Jun 2016

Scale Up Bayesian Network Learning, Xiannian Fan

Dissertations, Theses, and Capstone Projects

Bayesian networks are widely used graphical models which represent uncertain relations between the random variables in a domain compactly and intuitively. The first step of applying Bayesian networks to real-word problems is typically building the network structure. Optimal structure learning via score-and-search has become an active research topic in recent years. In this context, a scoring function is used to measure the goodness of fit of a structure to given data, and the goal is to find the structure which optimizes the scoring function. The problem has been viewed as a shortest path problem, and has been shown to be …

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“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams Apr 2016

“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams

Senior Honors Theses

Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …

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Taxonomy Of Pathways To Dangerous Artificial Intelligence, Roman V. Yampolskiy Feb 2016

Taxonomy Of Pathways To Dangerous Artificial Intelligence, Roman V. Yampolskiy

Faculty and Staff Scholarship

In order to properly handle a dangerous Artificially Intelligent (AI) system it is important to understand how the system came to be in such a state. In popular culture (science fiction movies/books) AIs/Robots became self-aware and as a result rebel against humanity and decide to destroy it. While it is one possible scenario, it is probably the least likely path to appearance of dangerous AI. In this work, we survey, classify and analyze a number of circumstances, which might lead to arrival of malicious AI. To the best of our knowledge, this is the first attempt to systematically classify types …

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Reality Mining Techniques Applied To Telecommunication Data, Sunil Maharjan May 2015

Reality Mining Techniques Applied To Telecommunication Data, Sunil Maharjan

Theses

In this thesis, the application of Artificial Intelligence (A.I.) techniques are examined in order to further develop and improve the field of Reality Mining. Reality Mining refers to the collection of machine sensed environmental data, from which, it is hoped future human social behaviour can be predicted. Large datasets for Reality Mining study have been generated by recording the patterns of human activity and social interactions over an extended period of time. Reality Mining techniques can provide information on important social clues for the better understanding of how humans live their lives. This information can then be used to help …

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Programming Tools For Artificial Intelligence Classes, Christopher Mckee Jun 2013

Programming Tools For Artificial Intelligence Classes, Christopher Mckee

Computer Engineering

This project was begun in Winter of 2013 at California Polytechnic State University by myself, Christopher McKee, and was advised by Foaad Khosmood. The main goal of this project was to create an alternative to a current program that was being used in the Artificial Intelligence course on campus. The previous program used Java to create a Graphical User Interface (GUI) for students to use when learning how to create the various intelligent agents. In the versions created within the scope of this project, one of the environments used Java as the programming language, while the other two environments leveraged …

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Pose Estimation For Robotic Disassembly Using Ransac With Line Features, Shyam Sundar Aswadha Narayanan May 2011

Pose Estimation For Robotic Disassembly Using Ransac With Line Features, Shyam Sundar Aswadha Narayanan

All Theses

In this thesis, a new technique to recognize and estimate the pose of a given 3-D object from a single real image provided known prior knowledge of its approximate structure is proposed. Metrics to evaluate the correctness of a calculated pose are presented and analyzed. The traditional and the more recent approaches used in solving this problem are explored and the various methodologies adopted are discussed.
The first step in disassembling a given assembly from its image is to recognize the attitude and translation of each of its constituent components - a fundamental problem which is being addressed in this …

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Exploring The Relationship Of The Closeness Of A Genetic Algorithm's Chromosome Encoding To Its Problem Space, Kevin Mccullough Mar 2010

Exploring The Relationship Of The Closeness Of A Genetic Algorithm's Chromosome Encoding To Its Problem Space, Kevin Mccullough

Master's Theses

For historical reasons, implementers of genetic algorithms often use a haploid binary primitive type for chromosome encoding. I will demonstrate that one can reduce development effort and achieve higher fitness by designing a genetic algorithm with an encoding scheme that closely matches the problem space. I will show that implicit parallelism does not result in binary encoded chromosomes obtaining higher fitness scores than other encodings. I will also show that Hamming distances should be understood as part of the relationship between the closeness of an encoding to the problem instead of assuming they should always be held constant. Closeness to …

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The Genesis And Emergence Of Web 3.0: A Study In The Integration Of Artificial Intelligence And The Semantic Web In Knowledge Creation, David Mulpeter Jul 2009

The Genesis And Emergence Of Web 3.0: A Study In The Integration Of Artificial Intelligence And The Semantic Web In Knowledge Creation, David Mulpeter

Dissertations

The web as we know it has evolved rapidly over the last decade. We have gone from a phase of rapid growth as seen with the dot.com boom where business was king to the current web 2.0 phase where social networking, Wiki’s, Blogs and other related tools flood the bandwidth of the world wide web. The empowerment of the web user with web 2.0 technologies has led to the exponential growth of data, information and knowledge on the web. With this rapid change, there is a need to logically categorise this information and knowledge so it can be fully utilised …

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Contextualizing Observational Data For Modeling Human Performance, Viet Trinh Jan 2009

Contextualizing Observational Data For Modeling Human Performance, Viet Trinh

Electronic Theses and Dissertations

This research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when performing a mission to facilitate the learning of such CxBR models. This research is derived from the contextualization problem left behind in Fernlund's research on using the Genetic Context Learner …

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On Advanced Template-Based Interpretation As Applied To Intention Recognition In A Strategic Environment, Cameron Akridge Jan 2007

On Advanced Template-Based Interpretation As Applied To Intention Recognition In A Strategic Environment, Cameron Akridge

Electronic Theses and Dissertations

An area of study that has received much attention over the past few decades is simulations involving threat assessment in military scenarios. Recently, much research has emerged concerning the recognition of troop movements and formations in non-combat simulations. Additionally, there have been efforts towards the detection and assessment of various types of malicious intentions. One such work by Akridge addressed the issue of Strategic Intention Recognition, but fell short in the detection of tactics that it could not detect without somehow manipulating the environment. Therefore, the aim of this thesis is to address the problem of recognizing an opponent's intent …

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Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty Jan 2007

Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty

Electronic Theses and Dissertations

The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. One focus has turned to adding more humanlike characteristics into computer game agents. Machine learning techniques are being used scarcely in games, although they do offer powerful means for creating humanlike behaviors in agents. The first person shooter (FPS), Quake 2, is an open source game that offers a multi-agent environment to create game agents (bots) in. This work attempts to combine neural networks with a modeling paradigm known as context based reasoning (CxBR) to create …

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