Engineering Commons^™

Combined Behavioral And Engineering Approach To Preventing Highway Fatalities, Benjamin Blandford, Reginald Souleyrette, Caitlin N. Pope, Tony Fields, Erin Lammers-Staats

Kentucky Transportation Center Research Report

Traditional, single-discipline highway safety approaches can be augmented through multidisciplinary approaches that consider both engineering and behavioral interventions (e.g., education, enforcement, public outreach campaigns). Leveraging a systems-based conceptual framework of roadway safety, multiple forms of statistical and geospatial analysis, and SPF modeling and network screening, this report proposes and demonstrates methods for unpacking the influence of behavioral-related factors on crash occurrences and outcomes. The primary focus is on behaviors targeted in the Strategic Highway Safety Plan — aggressive driving, distracted driving, impaired driving, and driving without proper restraint (i.e., seatbelts). Based on application of these methods, the report highlights ...

When Engine(S) Go Silent: Speed-To-Fly For Airplane And Glider Pilots, Nihad Daidzic,

Aviation Department Publications

FAA Safety Seminar/Webinar (GL15xxxxxx); Master Knowledge 2 - 1 Credit.

Approach To Problem Solving And Use Of Intuition By Engineering Technology Students, Meher R. Taleyarkhan, Anne M. Lucietto, Natalie L. F. Hobson, Therese M. Azevedo

Journal of Global Education and Research

Engineering technology students often forgo a methodical approach of solving or answering questions on assignments or exams in favor of an intuition-based approach, emphasizing educated guessing (Broberg et al., 2008). Faculty observations have noted these student solutions often provide explanations, usually sans calculations, to support answers the students believe to be reasonable when in reality deviated from the correct answer. An extensive study was developed to assess several distinctions between student intuition and use of cognition in problem solving, as related to a generalized student population. The study was comprised of a survey and interview. The survey utilized two instruments ...

Proposal For And Validation Of Novel Risk-Based Process To Reduce The Risk Of Construction Site Fatalities (Major Accident Prevention (Map) Program), Roberta Selleck, Marcus Cattani, Maureen Hassall

Research outputs 2022 to 2026

Despite developments in the prevention of fatalities in the construction industry, fatalities resulting from well-known hazards continue at an unacceptable rate. Construction fatality prevention literature describes risk management techniques to provide ‘early warning’ of potential events. In dynamic construction project environments, these ‘early warnings’ are missed resulting in serious and fatal events. Critical Control Risk Management (CCRM) provides an alternative strategy to prevent fatal events in the construction industry. However, no research exists that explores the application of CCRM to actual construction projects. This study aims to design, develop, and validate a construction fatality prevention program using CCRM principles through ...

Like You Search, Gipson Bachman

LMU/LLS Theses and Dissertations

As consumers continue to make their purchases solely online without visiting brick-and-mortar stores, they increasingly look for ways to “touch, feel and try on” products without actually doing so. We believe social media influencers provide a way to do this, with the influencers themselves acting as “stand-ins” for consumers in their place. Finding influencers that look like you in 2022 sounds like it would be easy, but it isn’t. Until now.

LIKE YOU aims to answer this gap in the market by creating a proprietary search engine that, through answering a few questions, recommends a list of influencers that ...

Topologically Optimized Electrodes For Electroosmotic Actuation, Jianwen Sun, Jianyu Zhang, Ce Guan, Teng Zhou, Shizhi Qian, Yongbo Deng

Mechanical & Aerospace Engineering Faculty Publications

Electroosmosis is one of the most used actuation mechanisms for the microfluidics in the current active lab-on-chip devices. It is generated on the induced charged microchannel walls in contact with an electrolyte solution. Electrode distribution plays the key role on providing the external electric field for electroosmosis, and determines the performance of electroosmotic microfluidics. Therefore, this paper proposes a topology optimization approach for the electrodes of electroosmotic microfluidics, where the electrode layout on the microchannel wall can be determined to achieve designer desired microfluidic performance. This topology optimization is carried out by implementing the interpolation of electric insulation and electric ...

An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density, Joachim Lohn-Jaramillo

Dartmouth College Ph.D Dissertations

Multiple-Object Tracking (MOT) methods are used to detect targets in individual video frames, e.g., vehicles, people, and other objects, and then record each unique target’s path over time. Current state-of-the-art approaches are extremely complex because most rely on extracting and comparing visual features at every frame to track each object. These approaches are geared toward high-difficulty-tracking scenarios, e.g., crowded airports, and require expensive dedicated hardware, e.g., Graphics Processing Units. In hardware-constrained applications, researchers are turning to older, less complex MOT methods, which reveals a serious scalability issue within the state-of-the-art. Crowded environments are a niche application ...

A Review On Nanomaterials And Nanohybrids Based Bio-Nanocomposites For Food Packaging, Kalpani Y. Perera, Amit K. Jaiswal, Swarna Jaiswal

Articles

With an increasing demand for a novel, eco-friendly, high-performance packaging material “bio-nanocomposites” has attracted great attention in recent years. The review article aims at to evaluating recent innovation in bio-nanocomposites for food packaging applications. The current trends and research over the last three years of the various bio-nanocomposites including inorganic, organic nanomaterials, and nanohybrids, which are suitable as food packaging materials due to their advanced properties such as high mechanical, thermal, barrier, antimicrobial, and antioxidant are described in detail. In addition, the legislation, migration studies, and SWOT analysis on bio-nanocomposite film have been discussed. It has been observed that the ...

Light Field Salient Object Detection: A Review And Benchmark, Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan

Computational Visual Media

Salient object detection (SOD) is a long-standing research topic in computer vision with increasing interest in the past decade. Since light fields record comprehensive information of natural scenes that benefit SOD in a number of ways, using light field inputs to improve saliency detection over conventional RGB inputs is an emerging trend. This paper provides the first comprehensive review and a benchmark for light field SOD, which has long been lacking in the saliency community. Firstly, we introduce light fields, including theory and data forms, and then review existing studies on light field SOD, covering ten traditional models, seven deep ...

Recent Advances In Glinty Appearance Rendering, Junqiu Zhu, Sizhe Zhao, Yanning Xu, Xiangxu Meng, Lu Wang, Ling-Qi Yan

Computational Visual Media

The interaction between light and materials is key to physically-based realistic rendering. However, it is also complex to analyze, especially when the materials contain a large number of details and thus exhibit "glinty" visual effects. Recent methods of producing glinty appearance are expected to be important in next-generation computer graphics. We provide here a comprehensive survey on recent glinty appearance rendering. We start with a definition of glinty appearance based on microfacet theory, and then summarize research works in terms of representation and practical rendering. We have implemented typical methods using our unified platform and compare them in terms of ...

Automatic Location And Semantic Labeling Of Landmarks On 3d Human Body Models, Shan Luo, Qitong Zhang, Jieqing Feng

Computational Visual Media

Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design. The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem. Inthis paper, a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks. A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity. A symmetry-awaredescriptor is proposed based on the structure of the human body models, which is robust to both pose and shape variations in ...

Constructing Self-Supporting Surfaces With Planar Quadrilateral Elements, Long Ma, Sidan Yao, Jianmin Zheng, Yang Liu, Yuanfeng Zhou, Shi-Qing Xin, Ying He

Computational Visual Media

We present a simple yet effective method for constructing 3D self-supporting surfaces with planar quadrilateral (PQ) elements. Starting with a triangular discretization of a self-supporting surface, we firstcompute the principal curvatures and directions of each triangular face using a new discrete differential geometryapproach, yielding more accurate results than existing methods. Then, we smooth the principal direction field to reduce the number of singularities. Next, we partition all faces into two groups in terms of principalcurvature difference. For each face with small curvature difference, we compute a stretch matrix that turns the principal directions into a pair of conjugate directions. For ...

Blnet: Bidirectional Learning Network For Point Clouds, Wenkai Han, Hai Wu, Chenglu Wen, Cheng Wang, Xin Li

Computational Visual Media

The key challenge in processing point clouds lies in the inherent lack of ordering and irregularity of the 3D points. By relying on per-point multi-layer perceptions (MLPs), most existing point-based approaches only address the first issue yet ignore the second one. Directly convolving kernels with irregular points will result in loss of shape information. This paper introduces a novel point-based bidirectional learning network (BLNet) to analyze irregular 3D points. BLNet optimizes the learning of 3D points through two iterative operations: feature-guided point shifting and feature learning from shifted points, so as to minimise intra-class variances, leading to a more regular ...

Joint Self-Supervised And Reference-Guided Learning For Depth Inpainting, Heng Wu, Kui Fu, Yifan Zhao, Haokun Song, Jia Li

Computational Visual Media

Depth information can benefit various computer vision tasks on both images and videos. However, depth maps may suffer from invalid values in many pixels, and also large holes. To improve such data, we propose a joint self-supervised and reference-guided learning approach for depth inpainting. For the self-supervised learning strategy, we introduce an improved spatial convolutional sparse coding module in which total variation regularization is employed to enhance the structural information while preserving edge information. This module alternately learns a convolutional dictionary and sparse coding from a corrupted depth map. Then, both the learned convolutional dictionary and sparse coding are convolved ...

Image-Guided Color Mapping For Categorical Data Visualization, Qian Zheng, Min Lu, Sicong Wu, Ruizhen Hu, Joel Lanir, Hui Huang

Computational Visual Media

Appropriate color mapping for categorical data visualization can significantly facilitate the discovery of underlying data patterns and effectively bring out visual aesthetics. Some systems suggest pre-defined palettes for this task. However, a predefined color mapping is not always optimal, failing to consider users’ needs for customization. Given an input cate-gorical data visualization and a reference image, we present an effective method to automatically generate a coloring that resembles the reference while allowing classes to be easily distinguished. We extract a color palette with high perceptual distance between the colors by sampling dominant and discriminable colors from the image’s color ...

Self-Supervised Coarse-To-Fine Monocular Depth Estimation Using A Lightweight Attention Module, Yuanzhen Li, Fei Luo, Chunxia Xiao

Computational Visual Media

Self-supervised monocular depth estimation has been widely investigated and applied in previous works. However, existing methods suffer from texture-copy, depth drift, and incomplete structure. It is difficult for normal CNN networks to completely understand the relationship between the object and its surrounding environment. Moreover, it is hard to design the depth smoothness loss to balance depth smoothness and sharpness. To address these issues, we propose a coarse-to-fine method with a normalized convolutional block attention module (NCBAM). In the coarse estimation stage, we incorporate the NCBAM into depth and pose networks to overcome the texture-copy and depth drift problems. Then, we ...

High Fidelity Virtual Try-On Network Via Semantic Adaptation And Distributed Componentization, Chenghu Du, Feng Yu, Minghua Jiang, Ailing Hua, Yaxin Zhao, Xiong Wei, Tao Peng, Xinrong Hu

Computational Visual Media

Image-based virtual try-on systems have significant commercial value in online garment shopping. However, prior methods fail to appropriately handle details, so are defective in maintaining the original appearance of organizational items including arms, the neck, and in-shop garments. We propose a novel high fidelity virtual try-on network to generate realistic results. Specifically, a distributed pipeline is used for simultaneous generation of organizational items. First, the in-shop garment is warped using thin plate splines (TPS) to give a coarse shape reference, and then a corresponding target semantic map is generated, which can adaptively respond to the distribution of different items triggered ...

Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things, Tarek Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venugopal Veeravalli

ACI Journal Articles

IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach ...

Student Engagement In An Online Engineering Afterschool Program During The Covid-19 Pandemic, Virginia Snodgrass Rangel, Jerrod A. Henderson, Chelsea Martinez, Rick Greer

Journal of Pre-College Engineering Education Research (J-PEER)

The COVID-19 pandemic forced much of schooling online and limited students’ access to informal learning opportunities such as afterschool programs. The purpose of this study was to investigate how fourth- and fifth-grade students engaged in an online engineering program and what factors influenced their engagement. We drew on a four-dimensional model of student engagement to describe how students engaged in the afterschool engineering program and to identify the factors that enhanced or inhibited engagement. Using a case study design, we drew on interviews with six program mentors and ten students and observation data from weekly Zoom sessions throughout the 2020 ...

Development Of An Excel Model To Evaluate The Stability Of Slopes, Bradley Davis

All Graduate Plan B and other Reports

This objective of this study is to determine a method or tool for taking given slope stability parameters and quickly and effectively determining the factor of safety against sliding of fully softened slopes. This study evaluates the effects of soil and geometric parameters of common slopes, and models these properties in a hypothetical model. The methodology is based on a parametric analysis using the Spencer’s Method of Slices limit equilibrium analysis used in the computer program Slide2. A parametric analysis is performed to determine which soil and/or geometric properties have a high influence on slope stability. The parametric ...