Artificial Intelligence and Robotics Commons^™

Research On Parametric Modeling And Deformation Method Of Human Muscle, Na Ni, Kunjin He, Xincheng Zhu, Zhengming Chen

Journal of System Simulation

Abstract: Due to the volume preserving constraint of human muscle in the deformation process, and the lack of three-dimensional multi-angle representation of muscle motion, a parametric modeling and deformation method of human muscle is proposed. Based on MRI (magnetic resonance imaging) data, the external contour line is extracted from the slice image generated by MRI data to construct a three-dimensional muscle model; muscle features are defined hierarchically, and the mapping relationship between semantic parameters is established to realize the volume preserving deformation of muscle; by establishing a vector-valued dynamic fourth-order differential equation, the feature curve dynamically simulates the process …

State Prediction Of Poverty Alleviation Objects Based On Hmm And Multidimensional Data, Jun He, Sunyan Hong, Yifang Zhou, Shikai Shen, Muquan Zou

Journal of System Simulation

Abstract: In order to solve the problems of inaccurate prediction of poverty, poverty reduction and poverty returen, and the difficulty in identifying the key factors affecting the state transition, 8 key features and 22 observed states are extracted from the poverty reduction basic data and multi-industry data. The relationship between observed state and implied state is constructed, and the hidden markov model (HMM) of poverty alleviation is established. Data of a deep poverty county for three consecutive years are used as samples for parameter training, test experiment and result verification. The results show that the method has a strong …

Simulation Of Navigation Process Based On Nonlinear Observer, Zhiwei Wang, Jizong Hu, Fengjie Wang, Jie Huang

Journal of System Simulation

Abstract: In order to solve the problem that the scope of using thetraditional observers is limited by assumptions, in the process of establishing the observer, a parameter projection relationship is designed and added to the observer to keep it under the condition of not being constrained by the assumptions. It is semi-globally stable, and the estimation process is more direct, which makes the parameter estimation process under nonlinear conditions converge faster. The simulation results show that the computational complexity of the nonlinear observer is reduced by nearly 80% compared with the multiplicative extended Kalman filter. The experimental results show that …

A Visual Analytics Of Urban Traffic Events Using Social Media Data, Xiangping Wu, Lijun Ping, Dongshi Xu

Journal of System Simulation

Abstract: Traffic text data in social media can supplement traffic flow information, for which a visual analysis method for traffic events is proposed. A text processing model is designed to process the social media data and extract the description information of traffic event. The vector representation of road node attributes is learned based on graph embedding algorithm, and a road similarity model is estbalished. A prediction model of the traffic event is built based on the road similarity and the kernel density model. An interactive visual analysis system is designed to carry out visual analysis. Though traffic …

Research On Visual Inspection Algorithm Of Crimping Appearance Defects For Wiring Harness Terminals, Bingan Yuan, Mingen Zhong, Jingxin Ni

Journal of System Simulation

Abstract: Aiming at the low efficiency and high missing rate of wiring harness terminals, an image detection method based on machine vision is proposed. The characteristic parameters of five typical defects in three main parts of wiring harness terminals are analyzed and defined. Tthe algorithms of extracting positioning datum, segmenting inspected-parts adaptively, extracting the defect features and calculating the characteristic parameters are designed respectively, and the defects criterions are given. The experimental results show that the algorithms are suitable for single defect and multi-class defects, both the miss detection rate and the false positiveness rate are low. The accuracy and …

Phased Array Radar Doa Estimation Simulation System Designed With Interactive Control, Fan Yu, Dongqi Luo, Binqiang Si, Jihong Zhu

Journal of System Simulation

Abstract: For the problem of simulation, evaluation and verification of phased array radar the direction of arrival (DOA) estimation of phased array radar, the modeling and evaluation of phased array radar DOA estimation is discussed. A real-time simulation system based on interactive control is designed. The simulation system can be used to model and simulate the interactive target & environment, phased array and target detection efficiency evaluation model. The signal generation, free space propagation, echo signal acquisition, signal processing and other processes can be simulated during the detection of real-time flying target, and the effect of DOA estimation can be …

Research On Immersive Virtual Reality Interactive System For Flow Visualization, Shijian Xu, Dan Zhao, Chengyu Su, Fupan Wang, Xiaorong Zhang, Fang Wang, Yadong Wu

Journal of System Simulation

Abstract: Aiming at the problem of low interaction efficiency due to the lack of depth information in the current desktop flow visualization application based on the two-dimensional display interaction environment, virtual reality technology is introduced to design and implement an immersive flow visualization system with diversified interaction methods. Based on the gaze and gesture interaction technology, the system designs and implements gesture-based navigation methods and three-dimensional interactive widgets based on user requirements, as well as immersive interactive panels based on user gaze and gestures. We designed and implemented an immersive interactive management method based on visual scenes and a visual …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

What Does It Take To Bake A Cake? The Reciperef Corpus And Anaphora Resolution In Procedural Text, Biaoyan Fang, Timothy Baldwin, Karin Verspoor

Natural Language Processing Faculty Publications

Procedural text contains rich anaphoric phenomena, yet has not received much attention in NLP. To fill this gap, we investigate the textual properties of two types of procedural text, recipes and chemical patents, and generalize an anaphora annotation framework developed for the chemical domain for modeling anaphoric phenomena in recipes. We apply this framework to annotate the RecipeRef corpus with both bridging and coreference relations. Through comparison to chemical patents, we show the complexity of anaphora resolution in recipes. We demonstrate empirically that transfer learning from the chemical domain improves resolution of anaphora in recipes, suggesting transferability of general procedural …

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

Problematic Ai — When Should We Use It?, Fredric Lederer

Popular Media

No abstract provided.

Du Undergraduate Showcase: Research, Scholarship, And Creative Works: Abstracts, Emma Aggeler, Elena Arroway, Daisy T. Booker, Justin Bravo, Kyle Bucholtz, Megan Burnham, Nicole Choi, Spencer Cockerell, Rosie Contino, Jackson Garske, Kaitlyn Glover, Caroline Hamilton, Haley Hartmann, Madalyne Heiken, Colin Holter, Leah Huzjak, Alyssa Jeng, Cole Jernigan, Chad Kashiwa, Adelaide Kerenick, Emily King, Abigail Langeberg, Maddie Leake, Meredith Lemons, Alec Mackay, Greer Mckinley, Ori Miller, Guy Milliman, Katherine Miromonti, Audrey Mitchell, Lauren Moak, Megan Morrell, Gelella Nebiyu, Zdenek Otruba, Toni V. Panzera, Kassidy Patarino, Sneha Patil, Alexandra Penney, Kevin Persky, Caitlin Pham, Gabriela Recinos, Mary Ringgenberg, Chase Routt, Olivia Schneider, Roman Shrestha, Arlo Simmerman, Alec Smith, Tessa Smith, Nhi-Lac Thai, Kyle Thurmann, Casey Tindall, Amelia Trembath, Maria Trubetskaya, Zachary Vangelisti, Peter Vo, Abby Walker, David Winter, Grayden Wolfe, Leah York

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Showcase.

The Behaviors Of Bert Attention Heads In Stereotype Detection, Joseph H. Hajjar

Dartmouth College Master’s Theses

We are living in the age of information, where it has become increasingly easy to share ideas, news, and content which are seen by an increasingly large number of people. This increasing scope of the increasing amount of data that is being shared lends itself to the question: how can we determine whether what we are reading promotes a stereotype? Previous work has applied transformer based models in this domain yielding impressive performance, but few studies exist interpreting the nature of attention heads in this task. Our work explores the feature encoding and extraction behaviors of attention heads in transformer …

Artificial Intelligence, Controls, And Sensor Fusion For Optimization And Modeling Of Space Missions And Particle Accelerators, Reza Pirayeshshirazinezhad

Mechanical Engineering ETDs

This PhD dissertation is devoted to developing artificial intelligence (AI) applications for space missions and particle accelerators considering constraints on the computational resources. The space mission studied in this research, the Virtual Telescope for X-ray Observations (VTXO), is the mission exploiting 2 6U-CubeSats operating in a precision formation. The goal of the VTXO project is to develop a space-based, X-ray imaging telescope with high angular resolution precision. VTXO space mission is designed and the mission is optimized to increase the performance of the mission. Trajectory optimization with AI, hybrid control, control algorithms, and high performance computing are all used to …

Human Trafficking And Machine Learning: A Data Pipeline From Law Agencies To Research Groups, Nathaniel Hites

Computer Science and Engineering Theses and Dissertations

Human trafficking is a form of modern-day slavery that, while highly illegal, is more dangerous with the advancements of modern technology (such as the Internet), which allows such a practice to spread more easily and quickly all over the world. While the number of victims of human trafficking is large (according to non-profit organization Safe House, there are estimated to be about 20.5 million human trafficking victims, worldwide (“Human Trafficking Statistics & Facts.” Safe Horizon)- co-erced or manipulated by traffickers into either forced labor, or sexual exploitation and encounters), the number of heard cases is proportionally low- several thousand successful …

Real Time Call-Flagging System To Respond To Suicidal Ideation In Call Centers, Vishnu Menon, Joseph Carrigan, Charles Floeder, Thomas Walton, Devin Mcguire

Honors Program: Senior Projects (Public)

The 2021-2022 Signature Performance Design Studio team developed a live audio call-flagging system that enables faster responses and new response pathways to veteran crises by call service representatives and their management team. Using a custom made deep learning model, live audio streaming server, and Teams broadcasting add-on, the system empowers Signature Performance call service representatives to make quicker and more well informed decisions to provide veteran’s the best care possible.

The Contribution Of Ethical Governance Of Artificial Intelligence & Machine Learning In Healthcare, Tina Nguyen

Electronic Theses and Dissertations

With the Internet Age and technology progressively advancing every year, the usage of Artificial Intelligence (AI) along with Machine Learning (ML) algorithms has only increased since its introduction to society. Specifically, in the healthcare field, AI/ML has proven to its end-users how beneficial its assistance has been. However, despite its effectiveness and efficiencies, AI/ML has also been under scrutiny due to its unethical outcomes. As a result of this, two polarizing views are typically debated when discussing AI/ML. One side believes that AI/ML usage should continue regardless of its unsureness, while the other side argues that this technology is too …

Incorporating Spatial Relationship Information In Signal-To-Text Processing, Jeremy Elon Davis

Theses and Dissertations

This dissertation outlines the development of a signal-to-text system that incorporates spatial relationship information to generate scene descriptions. Existing signal-to-text systems generate accurate descriptions in regards to information contained in an image. However, to date, no signalto- text system incorporates spatial relationship information. A survey of related work in the fields of object detection, signal-to-text, and spatial relationships in images is presented first. Three methodologies followed by evaluations were conducted in order to create the signal-to-text system: 1) generation of object localization results from a set of input images, 2) derivation of Level One Summaries from an input image, and …

Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley

University of Cincinnati Law Review

No abstract provided.