Computer Engineering Commons^™

From Decoder Rings To Deep Fakes: Translating Complex Technologies For Legal Education, Rachel S. Evans, Jason Tubinis

Presentations

“Technological developments are disrupting the practice of law” is a common refrain, but the last few years has seen some particularly complex pieces of technology become the hot new thing in legal tech. This session will look at blockchain, quantum computing, artificial intelligence, and ‘Deep Fakes’ as examples of how librarians can stay abreast of technological developments and inform themselves about their impacts in the legal profession. Then we will look at how to translate the complexities and jargon of these examples into lessons for for-credit courses, one-off informational sessions, or meetings with stakeholders.

Recipe For Disaster, Zac Travis

MFA Thesis Exhibit Catalogs

Today’s rapid advances in algorithmic processes are creating and generating predictions through common applications, including speech recognition, natural language (text) generation, search engine prediction, social media personalization, and product recommendations. These algorithmic processes rapidly sort through streams of computational calculations and personal digital footprints to predict, make decisions, translate, and attempt to mimic human cognitive function as closely as possible. This is known as machine learning.

The project Recipe for Disaster was developed by exploring automation in technology, specifically through the use of machine learning and recurrent neural networks. These algorithmic models feed on large amounts of data as a …

Research On Interaction Model Of Hand Tracking Based On Cognitive Theory, Shaobai Zhang, Zhang Teng

Journal of System Simulation

Abstract: This paper aims to solve the problems in a vector integration to endpoint (VITE) model of human reaching and grasping under perturbations of object size, distance and orientation. We discuss how to reduce the numbers of disturbances of three main kinds of components: hand/wrist transport, grip aperture and hand orientation. Based on the achievements of cognitive psychology, and a tracking and cognitive model for operational 3D gestures, this paper proposes a new divide-and-conquer model that is used for indicating current grasping status and to trigger three main kinds of methods of when to start or stop working. The model …

From Situation Cognition Stepped Into Situation Intelligent Cognition, Zhu Feng, Xiaofeng Hu, Wu Lin, Xiaoyuan He, Xuezhi Lü, Liao Ying

Journal of System Simulation

Abstract: Aimed at operational situation cognition and some relevant problems under the background of the Joint-Tactical, some deep researches are carried out in this paper. The concept models of combat situation cognition and situation intelligent cognition are proposed respectively, and some related concepts are clarified. The situation intelligent cognition technology framework is proposed, and five key problems which should be solved are analyzed, and the possible technical routes are given. These research contents and achievements build a foundation for stepping into the situation intelligent cognition from combat situation cognition.

Preliminary Study Of Modeling And Simulation Technology Oriented To Neo-Type Artificial Intelligent Systems, Libo Hu, Xudong Chai, Zhang Lin, Li Tan, Duzheng Qing, Tingyu Lin, Liu Yang

Journal of System Simulation

Abstract: A brief interpretation of the rapidly developing “New Internet+ Big Data+ Artificial Intelligence+” era is given in the paperand the essence and the architectureof neo-type artificial intelligence systems are explained. The meaning of neo-type artificial intelligence system oriented modelling and simulation technology is proposed and the new challenges they are facing are discussed. The research contents and preliminaryresults on neo-type artificial intelligence system oriented modelling and simulation technology are given, which includeneo-type artificial intelligence system oriented modelling/secondary modelling, intelligent simulation computer, smart cloud simulation and intelligent simulation hardware/software supporting system technology, and intelligent simulation system application engineering technology. Several …

Multi-Sensory Deep Learning Architectures For Slam Dunk Scene Classification, Paul Minogue

Dissertations

Basketball teams at all levels of the game invest a considerable amount of time and effort into collecting, segmenting, and analysing footage from their upcoming opponents previous games. This analysis helps teams identify and exploit the potential weaknesses of their opponents and is commonly cited as one of the key elements required to achieve success in the modern game. The growing importance of this type of analysis has prompted research into the application of computer vision and audio classification techniques to help teams classify scoring sequences and key events using game footage. However, this research tends to focus on classifying …

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 …

Communications Using Deep Learning Techniques, Priti Gopal Pachpande

Legacy Theses & Dissertations (2009 - 2024)

Deep learning (DL) techniques have the potential of making communication systems

Should Robots Prosecute And Defend?, Stephen E. Henderson

Faculty Articles

Even when we achieve the ‘holy grail’ of artificial intelligence—machine intelligence that is at least as smart as a human being in every area of thought—there may be classes of decisions for which it is intrinsically important to retain a human in the loop. On the common account of American criminal adjudication, the role of prosecutor seems to include such decisions given the largely unreviewable declination authority, whereas the role of defense counsel would seem fully susceptible of automation. And even for the prosecutor, the benefits of automation might outweigh the intrinsic decision-making loss, given that the ultimate decision—by judge …

A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall

Electrical & Computer Engineering and Computer Science Faculty Publications

For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …

Cloud-Supported Machine Learning System For Context-Aware Adaptive M-Learning, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq

Turkish Journal of Electrical Engineering and Computer Sciences

It is a knotty task to amicably identify the sporadically changing real-world context information of a learner during M-learning processes. Contextual information varies greatly during the learning process. Contextual information that affects the learner during a learning process includes background knowledge, learning time, learning location, and environmental situation. The computer programming skills of learners improve rapidly if they are encouraged to solve real-world programming problems. It is important to guide learners based on their contextual information in order to maximize their learning performance. In this paper, we proposed a cloud-supported machine learning system (CSMLS), which assists learners in learning practical …

Combining Algorithms For More General Ai, Mark Robert Musil

Maseeh Summer Undergraduate Research Experience

Two decades since the first convolutional neural network was introduced the AI sub-domains of classification, regression and prediction still rely heavily on a few ML architectures despite their flaws of being hungry for data, time, and high-end hardware while still lacking generality. In order to achieve more general intelligence that can perform one-shot learning, create internal representations, and recognize subtle patterns it is necessary to look for new ML system frameworks. Research on the interface between neuroscience and computational statistics/machine learning has suggested that combined algorithms may increase AI robustness in the same way that separate brain regions specialize. In …

A Qualitative Research On Marketing And Sales In The Artificial Intelligence Age, Yin Yang, Keng Siau

Research Collection School Of Computing and Information Systems

The age of artificial intelligence is here! Artificial Intelligence, robotics, machine learning, and automation are impacting the field of marketing and sales in an unprecedented way. In this study, the qualitative research methodology will be used to better understand the revolution and evolution of marketing and sales field in the AI age. Multiple case studies will be performed in various marketing and sales units in different organizations. This research is of value to both academics and practitioners as it aims to provide a detailed analysis and documentation of the changes in marketing and sales functionalities and job markets as AI …

Plant Identification Using Tensorflow, Kody G. Dangtongdee

Computer Engineering

Exploring the diverse nature that is available in San Luis Obispo is one of my favorite activities, however, I often am frustrated that I am unable to identify or learn more about the plants that I appreciate. This project is an attempt at using the concepts of neural networks to create an image classifier which can identify plants. Machine learning is one of the biggest topics in computer science at the moment, and its many uses make it a topic that will continue to be researched for a very long time. Convolutional neural networks are a popular realm of machine …

Cyber-Physical Embedded Systems With Transient Supervisory Command And Control: A Framework For Validating Safety Response In Automated Collision Avoidance Systems, Daniel K. Trembley

Graduate Dissertations and Theses

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness …

Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophiclogic,symboliclogic,set,probability,statistics,etc.,are,respectively,generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on. Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in computational intelligence, multiple-attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc. This Special Issue gathers original research papers that report on the state of the art, as well as on recent advancements in neutrosophic information theory in soft computing, artificial intelligence, …

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon

Browse all Theses and Dissertations

Goals can be described as the user's desired state of the agent and the world and are satisfied when the agent and the world are altered in such a way that the present state matches the desired state. For physical agents, they must act in the world to alter it in a series of individual atomic actions. Traditionally, agents use planning to create a chain of actions each of which altering the current world state and yielding a new one until the final action yields the desired goal state. Once this goal state has been achieved, the goal is said …

Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi

Electronic Theses and Dissertations

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …

Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Domains such as disaster rescue, security patrolling etc. often feature dynamic environments where allocations of tasks to agents become ineffective due to unforeseen conditions that may require agents to leave the team. Agents leave the team either due to arrival of high priority tasks (e.g., emergency, accident or violation) or due to some damage to the agent. Existing research in task allocation has only considered fixed number of agents and in some instances arrival of new agents on the team. However, there is little or no literature that considers situations where agents leave the team after task allocation. To that …

Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu

Research Collection School Of Computing and Information Systems

Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …

Models For Pedestrian Trajectory Prediction And Navigation In Dynamic Environments, Jeremy N. Kerfs

Master's Theses

Robots are no longer constrained to cages in factories and are increasingly taking on roles alongside humans. Before robots can accomplish their tasks in these dynamic environments, they must be able to navigate while avoiding collisions with pedestrians or other robots. Humans are able to move through crowds by anticipating the movements of other pedestrians and how their actions will influence others; developing a method for predicting pedestrian trajectories is a critical component of a robust robot navigation system. A current state-of-the-art approach for predicting pedestrian trajectories is Social-LSTM, which is a recurrent neural network that incorporates information about neighboring …

Adapting The Search Space While Limiting Damage During Learning In A Simulated Flapping Wing Micro Air Vehicle, Monica Sam

Browse all Theses and Dissertations

Cyber-Physical Systems (CPS) are characterized by closely coupled physical and software components that operate simultaneously on different spatial and temporal scales; exhibit multiple and distinct behavioral modalities; and interact with one another in ways not entirely predictable at the time of design. A commonly appearing type of CPS are systems that contain one or more smart components that adapt locally in response to global measurements of whole system performance. An example of a smart component robotic CPS system is a Flapping Wing Micro Air Vehicle (FW-MAV) that contains wing motion oscillators that control their wing flapping patterns to enable the …

Internet Of Things To Smart Iot Through Semantic, Cognitive, And Perceptual Computing, Amit P. Sheth

Publications

Rapid growth in the Internet of Things (IoT) has resulted in a massive growth of data generated by these devices and sensors put on the Internet. Physical-cyber-social (PCS) big data consist of this IoT data, complemented by relevant Web-based and social data of various modalities. Smart data is about exploiting this PCS big data to get deep insights and make it actionable, and making it possible to facilitate building intelligent systems and applications. This article discusses key AI research in semantic computing, cognitive computing, and perceptual computing. Their synergistic use is expected to power future progress in building intelligent systems …

Pure Fuzzy Hall Effect Sensors For Permanent Magnet Synchronous Motor, İbrahi̇m Alişkan, Rüstem Yilmazel

Turkish Journal of Electrical Engineering and Computer Sciences

An investigation about Hall effect sensors' efficiency is confirmed in permanent magnet synchronous motor (PMSM) drive systems. A fuzzy control algorithm is used as an artificial intelligence controller. Large scale and low slopes are used for creating membership functions and a sensitive controller is obtained. Speed is wanted to be taken under control and a minimum error value is aimed. PMSM drive systems are established using MATLAB-Simulink/SimPower. Simulations are realized with real-time parameters in discrete mode. A fuzzy logic controller is designed by using the MATLAB/Fuzzy Logic Toolbox. A normalization technique and high resolution output of the fuzzy logic controller …

Pathfinding In Computer Games, Ross Graham, Hugh Mccabe, Stephen Sheridan

The ITB Journal

One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core of any AI movement system. This report will highlight pathfinding algorithms used presently in games and their shortcomings especially when dealing with real-time pathfinding. With the advances being made in other components, such as physics engines, it is AI that is impeding the next generation of computer games. This report will focus on how machine learning techniques such as Artificial Neural Networks and Genetic Algorithms can be used to enhance an agents ability …

A Java Framework For Computer Vision, Stephen Sheridan

The ITB Journal

This paper outlines a framework implemented entirely in Java that attempts to give students exposure to computer vision systems from a practical standpoint. Various tools and technologies are introduced that will allow a student to acquire an input image through a WebCam, extract useful information from that input image and finally, attempt to make sense of the input.

The Design And Implementation Of An Adaptive Chess Game, Mehdi Peiravi

Electronic Theses, Projects, and Dissertations

In recent years, computer games have become a common form of entertainment. Fast advancement in computer technology and internet speed have helped entertainment software developers to create graphical games that keep a variety of players’ interest. The emergence of artificial intelligence systems has evolved computer gaming technology in new and profound ways. Artificial intelligence provides the illusion of intelligence in the behavior of NPCs (Non-Playable-Characters). NPCs are able to use the increased CPU, GPU, RAM, Storage and other bandwidth related capabilities, resulting in very difficult game play for the end user. In many cases, computer abilities must be toned down …

Novelty Wins, “Straight Toward Objective” Loses! Or Book Review: Why Greatness Cannot Be Planned: The Myth Of The Objective, By Kenneth O. Stanley And Joel Lehman, Reuben Hersh

Journal of Humanistic Mathematics

Experiments in evolutionary artificial intelligence demonstrate that progress toward an important, difficult goal is not best achieved by attempting to go directly toward that goal, but rather, by rewarding novelty.

A Theory Of Name Resolution, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

We describe a language-independent theory for name binding and resolution, suitable for programming languages with complex scoping rules including both lexical scoping and modules. We formulate name resolution as a two-stage problem. First a language-independent scope graph is constructed using language-specific rules from an abstract syntax tree. Then references in the scope graph are resolved to corresponding declarations using a language-independent resolution process. We introduce a resolution calculus as a concise, declarative, and language- independent specification of name resolution. We develop a resolution algorithm that is sound and complete with respect to the calculus. Based on the resolution calculus we …