Computer Engineering Commons^™

Nautilus Rov Robot Manipulator, Dana Stefanides, Jenny Huynh, Andrew Stewart, Steven Reimer, Andrew Nguyen, Rebecca Walters, Matt Hayes

Interdisciplinary Design Senior Theses

Global warming and climate change are prevalent issues in today’s society. As a result, research in the ocean, our world’s biggest ecosystem, is imperative in efforts to protect the environment. Santa Clara University’s Robotic Systems Lab contributes to this field through work and developments on remotely operated vehicles (ROVs). An existing ROV system called Nautilus consists of a robot arm, end effector, and storage system in order to collect various types of sediments at a depth of 300 feet. However, the previous system does not meet that requirement. In direct collaboration with researchers within the Monterey Bay Aquarium Research Institute, …

Assessing High Dynamic Range Imagery Performance For Object Detection In Maritime Environments, Erasmo Landaeta

Doctoral Dissertations and Master's Theses

The field of autonomous robotics has benefited from the implementation of convolutional neural networks in vision-based situational awareness. These strategies help identify surface obstacles and nearby vessels. This study proposes the introduction of high dynamic range cameras on autonomous surface vessels because these cameras capture images at different levels of exposure revealing more detail than fixed exposure cameras. To see if this introduction will be beneficial for autonomous vessels this research will create a dataset of labeled high dynamic range images and single exposure images, then train object detection networks with these datasets to compare the performance of these networks. …

Enhancing Cyberspace Monitoring In The United States Aviation Industry: A Multi-Layered Approach For Addressing Emerging Threats, Matthew Janson

Doctoral Dissertations and Master's Theses

This research project examined the cyberspace domain in the United States (U.S.) aviation industry from many different angles. The research involved learning about the U.S. aviation cyberspace environment, the landscape of cyber threats, new technologies like 5G and smart airports, cybersecurity frameworks and best practices, and the use of aviation cyberspace monitoring capabilities. The research looked at how vulnerable the aviation industry is from cyber-attacks, analyzed the possible effects of cyber-attacks on the industry, and suggests ways to improve the industry's cybersecurity posture. The project's main goal was to protect against possible cyber-attacks and make sure that the aviation industry …

The Exigency And How To Improve And Implement International Humanitarian Legislations More Advantageously In Times Of Both Cyber-Warfare And Cyberspace, Shawn J. Lalman

Doctoral Dissertations and Master's Theses

This study provides a synopsis of the following topics: the prospective limiters levied on cyber-warfare by present–day international legislation; significant complexities and contentions brought up in the rendering & utilization of International Humanitarian Legislation against cyber-warfare; feasible repercussions of cyber-warfare on humanitarian causes. It is also to be contended and outlined in this research study that non–state actors can be held accountable for breaches of international humanitarian legislation committed using cyber–ordnance if sufficient resources and skill are made available. It details the factors that prosecutors and investigators must take into account when organizing investigations into major breaches of humanitarian legislation …

Neural Network Fusion Of Multi-Modal Sensor Data For Autonomous Surface Vessels, David J. Thompson

Doctoral Dissertations and Master's Theses

Autonomous surface vessels (ASV) can potentially improve the safety of vessels traditionally operated by humans. Despite advancements in autonomous on-road vehicles, many of these advancements have yet to be realized for ASVs. This is primarily due to lacking ASV sensing platforms and public datasets for ASV-based perception research. To that end, this dissertation demonstrates the design of a synchronized multi-modal sensing platform for ASVs utilizing GPS/INS, LiDAR, LWIR cameras, HDR camera, and high-resolution cameras. The sensing platform is designed to maximize the overlap of sensors for multi-modal research and provides accurate intrinsic and extrinsic calibration between each sensor. Furthermore, the …

Run Toward The Incident: Collaboration Between Academia And Law Enforcement For Cybersecurity, Center For Cybersecurity, Stanley Mierzwa

Center for Cybersecurity

Collaboration and partnership between academia and law enforcement can bring about positive contributions for future research and activities in cybersecurity.

A Study Of Issues And Mitigations On Ddos And Medical Iot Devices, Jing-Chiou Liou, Robin Singh

Center for Cybersecurity

The Internet of Things (IoT) devices are being used heavily as part of our everyday routines. Through improved communication and automated procedures, its popularity has assisted users in raising the quality of work. These devices are used in healthcare in order to better collect the patient's data for their treatment. .

Research Days Poster: Cyberbullying Detection Utilizing Artificial Intelligence And Machine Learning, Annaliese Watson, Aysha Gardner, Dahana Moz Ruiz

Center for Cybersecurity

Technology is a tool that can be used to gain knowledge and for advancements in areas like medicine, machinery, and everyday tasks. It can be used to connect with friends, work from home, and to improve quality of life. But some social media users can use it to hurt others. Cyberbullying is a major issue that has been steadily growing over the past few years. Cyberbullying has also steadily increased the rates of stress, anxiety, depression, violent behavior, low self-esteem and may cause suicide. Cyberbullying is an ongoing problem for social media users, and it is urgent that a solution …

Research Days Poster: Security Operation Center, Jaineel A. Shah, Jing-Chiou Liou

Center for Cybersecurity

A Security Operations Center (SOC) is an organizational framework for cybersecurity, staffed by cybersecurity professionals who monitor an organization's security, analyze potential or current breaches, and respond accordingly. The SOC's goal is to diagnose, evaluate, and respond to cybersecurity events using technology solutions and established procedures. SOCs mainly operate 24/7, with security analysts monitoring environmental data for emerging threats and responding as needed. The SOC manages and enhances an organization's overall security posture.

Research Days Poster: A Study On Ransomware And Possible Mitigations, Robin Singh, Jing-Chiou Liou

Center for Cybersecurity

Ransomware is a quite violent attack that has been persistent throughout the industry for so many years. This malware doesn’t only affect the regular computer users but it has been targeting the big organizations and businesses also. Ransomware (ransom software) is a subset of malware designed to restrict access to a system or data until a requested ransom amount from the attacker is satisfied [2].In this poster, we will go over our findings on ransomware spreads, its actions, exploited vulnerabilities and few mitigation to reduce the impact of infection.

Research Days Poster: An Analysis Of Sql Injection Techniques, Uko Ebreso, Pankati Patel, Jing-Chiou Liou

Center for Cybersecurity

Storing information in a database allows web applications to operate with users who have their information stored online. ● The retrieval of information from the database is done using Structured Query Language (SQL) - a language used by the database that allows for data manipulation. ● SQL Injection (SQLIi) is an attack on a susceptible system using SQl which results in a loss of confidentiality, authentication, authorization and integrity of the software/system.

Metabolomic Differentiation Of Tumor Core And Edge In Glioma., Mary E. Baxter

Electronic Theses and Dissertations

Glioma is one of the most aggressive forms of brain cancer. It has been shown that the microenvironments differ significantly between the core and edge regions of glioma tumors. This study obtained metabolomic profiles of glioma core and edge regions using paired glioma core and edge tissue samples from 27 human patients. Data was acquired by performing liquid-liquid metabolite extraction and 2DLC-MS/MS on the tissue samples. In addition, a boosted generalized linear machine learning model was employed to predict the metabolomic profiles associated with O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation.

A panel of 66 metabolites was found to be statistically significant …

Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus

Engineering Faculty Articles and Research

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

A Survey Of Text Representation And Embedding Techniques In Nlp, Rajvardhan Patil, Sorio Boit, Venkat Gudivada, Jagadeesh Nandigam

Open Access Publishing Support Funded Articles

Natural Language Processing (NLP) is a research field where a language in consideration is processed to understand its syntactic, semantic, and sentimental aspects. The advancement in the NLP area has helped solve problems in the domains such as Neural Machine Translation, Name Entity Recognition, Sentiment Analysis, and Chatbots, to name a few. The topic of NLP broadly consists of two main parts: the representation of the input text (raw data) into numerical format (vectors or matrix) and the design of models for processing the numerical data. This paper focuses on the former part and surveys how the NLP field has …

Secure Reconfigurable Computing Paradigms For The Next Generation Of Artificial Intelligence And Machine Learning Applications, Brooks Olney

USF Tampa Graduate Theses and Dissertations

The fields of artificial intelligence (AI) and machine learning (ML) have been popular tools for data analysis at the edge, particularly through complex deep and convolutional neural networks (DNNs/CNNs), which can learn to parameterize a function given a labeled dataset. Indeed, these technologies have enabled significant progress across a wide range of fields and are becoming ubiquitous. However, training the best model for an application and subsequently using them to evaluate data in real-time requires an immense amount of computational power. Typically, ``smart" sensors at the edge rely on the cloud to accelerate this computation due to power and compute …

A Human-In-The-Loop Robot Grasping System With Grasp Quality Refinement, Tian Tan

USF Tampa Graduate Theses and Dissertations

The goal of this dissertation is to develop a grasping system for assistive robots that can help people with disabilities and the elderly to perform tasks of daily living. In developing this robot grasping system, we maximize its reliability, accuracy, and autonomy. High reliability and accuracy are required for robots to perform tasks around human users and to safely interact with objects that might be fragile or have contents that could spill. High autonomy is desired as users with disabilities are usually not dexterous enough to directly operate the robot. In this dissertation, a human-in-the-loop (HitL) robot grasping system is …

Artificial Neural Network-Based Prediction Assessment Of Wire Electric Discharge Machining Parameters For Smart Manufacturing, Itagi Vijayakumar Manoj, Sannayellappa Narendranath, Peter Madindwa Mashinini, Hargovind Soni, Shanay Rab, Shadab Ahmad, Ahatsham Hayat

Department of Electrical and Computer Engineering: Faculty Publications

Artificial intelligence (AI), robotics, cybersecurity, the Industrial Internet of Things, and blockchain are some of the technologies and solutions that are combined to produce “smart manufacturing,” which is used to optimize manufacturing processes by creating and/or accepting data. In manufacturing, spark erosion technique such as wire electric discharge machining (WEDM) is a process that machines different hard-to-cut alloys. It is regarded as the solution for cutting intricate parts and materials that are resistant to conventional machining techniques or are required by design. In the present study, holes of different radii, i.e. 1, 3, and 5mm, have been cut on Nickelvac-HX. …

Accurate Indoor Navigation System Based On Imu/Lp-Mm Integrated Method Using Kalman Filter Algorithm, Abdullah Mohammed Bahasan

Hadhramout University Journal of Natural & Applied Sciences

Abstract

The demand for navigation systems is rapidly increasing, especially in indoor environments which the signal of GPS is not available. Therefore the Inertial Measurement Unit (IMU) system is a suitable navigation system in such indoor environments. It usually consists of three accelerometers and three gyroscopes to determine position, velocity and attitude information, respectively, without need of any external source. But this type of navigation systems has errors growth with time due to accelerometers and gyroscopes drifts. This paper introduces indoor navigation system based on integrated IMU navigation system with proposed system called Landmarks Points-Map Matching (LP-MM) system using Kalman …

Deep Reinforcement Learning For Articulatory Synthesis In A Vowel-To-Vowel Imitation Task, Denis Shitov, Elena Pirogova, Tadeusz A. Wysocki, Margaret Lech

Department of Electrical and Computer Engineering: Faculty Publications

Articulatory synthesis is one of the approaches used for modeling human speech production. In this study, we propose a model-based algorithm for learning the policy to control the vocal tract of the articulatory synthesizer in a vowel-to-vowel imitation task. Our method does not require external training data, since the policy is learned through interactions with the vocal tract model. To improve the sample efficiency of the learning, we trained the model of speech production dynamics simultaneously with the policy. The policy was trained in a supervised way using predictions of the model of speech production dynamics. To stabilize the training, …

Realization Of Multi-Valued Logic Using Optical Quantum Computing, Sophie Choe

Dissertations and Theses

Quantum computing is a paradigm of computing using physical systems, which operate according to quantum mechanical principles. Since 2017, functioning quantum processing units with limited capabilities are available on the cloud. There are two models of quantum computing in the literature: discrete variable and continuous variable models. The discrete variable model is an extension of the binary logic of digital computing with quantum bits |0⟩ and |1⟩ . In the continuous variable model, the quantum state space is infinite-dimensional and the quantum state is expressed with an infinite number of basis elements.

In the physical implementation of quantum computing, however, …

Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps), Juan E. Nunez, Roger W. Tchegui Donfack, Rohit Rohit, Hayley Horn

SMU Data Science Review

Today, there is an increased risk to data privacy and information security due to cyberattacks that compromise data reliability and accessibility. New machine learning models are needed to detect and prevent these cyberattacks. One application of these models is cybersecurity threat detection and prevention systems that can create a baseline of a network's traffic patterns to detect anomalies without needing pre-labeled data; thus, enabling the identification of abnormal network events as threats. This research explored algorithms that can help automate anomaly detection on an enterprise network using Canadian Institute for Cybersecurity data. This study demonstrates that Neural Networks with Bayesian …

Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu

Journal of System Simulation

Abstract: A predictive depth deterministic policy gradient (PDDPG) algorithm is proposed by combining the least squares method with deep deterministic policy gradient(DDPG) for the problems of strong randomness, poor real-time performance, and slow planning speed by obstacle avoidance on aircraft carrier deck. The short-term trajectory of dynamic obstacles on the deck is predicted by the least square method. DDPG is used to provide agents with the ability to learn and make decisions in continuous space by the short-term trajectory of dynamic obstacles. The reward function is set based on the artificial potential field to improve the convergence speed and accuracy …

Floor Evacuation Simulation Based On Bim And Mr, Zhijie Li, Shuangyu Ma, Changhua Li, Xiao Liang, Jie Zhang

Journal of System Simulation

Abstract: Facing with the problem that the floor evacuation simulation only annotates the floor plan route, which is relatively single and not intuitive, a 3D building evacuation simulation method integrating mixed reality and building information model is proposed. The BIM components are reasonably planned and segmented, and reasonable annotation is performed. The BIM information is routed through the surface area heuristic optimization algorithm based on the bounding volume hierarchy. The evacuation simulation process is imported into the Microsoft Hololens2 hardware platform using the Unity3D development engine. The experimental results show that, compared with the previous evacuation simulation expressed only …

Multiagent Following Multileader Algorithm Based On K-Means Clustering, Guodong Yuan, Ming He, Ziyu Ma, Weishi Zhang, Xueda Liu, Wei Li

Journal of System Simulation

Abstract: Three K-means clustering algorithms are proposed to prevent chaos in the formation of a multi-agent system (MAS) with multiple leaders. The algorithm divides the cluster into communities with the same number of leaders, and the agents within the community will follow the same leader. Among the three proposed algorithms, algorithm #1 is suitable for scenarios with widely distributed agents wherein rapid consensus can be achieved in the shortest time; algorithm #2 is suitable for scenarios with a sparse agent distribution and effectively prevented agent collisions; and algorithm #3 exhibits rapid convergence and considerably reduces the MAS control cost, …

Costume Pattern Sketch Colorization And Style Transfer Based On Neural Network, Xingquan Cai, Zhijun Li, Mengyao Xi, Haiyan Sun

Journal of System Simulation

Abstract: Aiming at the problems of color overflow in pattern sketch colorization and lack of fabric texture features in style transfer, this paper proposes a method of costume pattern sketch colorization and style transfer based on neural network. This paper initializes the data set, collects the costume pattern image, extracts the costume pattern sketch, synthesizes the costume pattern sketch with color features and constructs the style data set. The research builds the conditional generative adversarial nets and achieves the costume pattern sketch with color features colorization based on the generator. The study constructs a convolutional neural network model, uses the …

Hyper-Heuristic Three Dimensional Eda For Solving Green Two-Sided Assembly Line Balancing Problem, Rong Hu, Shuai Ding, Bin Qian, Changsheng Zhang

Journal of System Simulation

Abstract: This paper establishes a model for green robotic two-sided assembly line balancing problem of type-I, and a hyper-heuristic three dimensional estimation of distribution algorithm (HH3DEDA) is proposed for solving this problem. In HH3DEDA, a combinatorial encoding rule based on process selectors is designed via considering the characteristics of the problem. Then, HH3DEDA with a high and low layered structure is proposed. In the upper layer, the three-dimensional probability matrix is utilized to learn high-quality high individual block structure and its distribution information, and then the matrix is sampled to generate new high level individuals. Each high individual is …

Research On Modeling And Solution Method Of Operational Tasks Optimization, Yue Ma, Lin Wu, Yun Liu, Guangzhao Ding

Journal of System Simulation

Abstract: Aiming at the problem of tasks optimization in operation task planning, this paper defines an operational tasks graph based on property graph and influence network to describe tasks, effects and their relationship. The model of operational tasks optimization is constructed based on the operational tasks graph, and the effect network transmission algorithm and resource constraint judgment algorithm are proposed. The problem is solved by the improved differential evolution algorithm. The experimental result shows that the operational tasks graph can vividly describe the relationship between operational tasks and effects, and the model and solution method are feasible and effective.

Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang

Journal of System Simulation

Abstract: In order to improve the convergence of multi-objective optimization algorithm and the diversity of optimization solution set, and alleviate the flown down of population in target space, a multi-objective optimization algorithm based on multi-attribute elite individual game mechanism is proposed. This paper uses Pareto dominance relationship and multi-index to comprehensively screen elite individuals. The elite individual game mechanism with K-means clustering is integrated with cross and mutation strategy, which effectively improves the convergence and diversity of the algorithm. A detailed convergence analysis of the algorithm is performed to prove the convergence of the algorithm. Eight representative comparison algorithms are …

Research On Decision Behavior Modeling Method Of Key Figures, Xiao Zheng, Xiaodong Peng, Minyu Lu, Tiejun Liu

Journal of System Simulation

Abstract: The decision-making of key figures is an important factor affecting the evolution of concerned events. The research on their decision-making behavior is of great significance for the prediction of important events. For the problem of decision behavior modeling and decision propensity prediction of key figures, the character attribute and measurement methods required for character modeling are analyzed, the character decision-making process and decision-making related influencing factors are analyzed, the exploration research of decision propensity prediction method is carried out, and the prediction model of decision propensity based on comprehensive interest characteristics and psychological characteristics is constructed. Through the research …