Engineering Commons^™

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 ...

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 ...

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 ...

Live Imaging Of Micro And Macro Wettability Variations Of Carbonate Oil Reservoirs For Enhanced Oil Recovery And Co/ Trapping/Storage, Anastasia Ivanova, A. Orekhov, S. Markovic, Stefan Iglauer, P. Grishin, A. Cheremisin

Research outputs 2022 to 2026

Carbonate hydrocarbon reservoirs are considered as potential candidates for chemically enhanced oil recovery and for CO² geological storage. However, investigation of one main controlling parameter—wettability—is usually performed by conventional integral methods at the core-scale. Moreover, literature reports show that wettability distribution may vary at the micro-scale due to the chemical heterogeneity of the reservoir and residing fluids. These differences may profoundly affect the derivation of other reservoir parameters such as relative permeability and capillary pressure, thus rendering subsequent simulations inaccurate. Here we developed an innovative approach by comparing the wettability distribution on carbonates at micro and macro-scale by ...

A Novel Microgrid Fault Detection And Classification Method Using Maximal Overlap Discrete Wavelet Packet Transform And An Augmented Lagrangian Particle Swarm Optimization-Support Vector Machine, Masoud Ahmadipour, Muhammad Murtadha Othman, Rui Bo, Zainal Salam, Hussein Mohammed Ridha, Kamrul Hasan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an intelligent method for fault detection and classification for a microgrid (MG) was proposed. The idea was based on the combination of three computational tools: signal processing using the maximal overlap discrete wavelet packet transform (MODWPT), parameter optimization by the augmented Lagrangian particle swarm optimization (ALPSO), and machine learning using the support vector machine (SVM). The MODWPT was applied to preprocess half cycle of the post-fault current samples measured at both ends of feeders. The wavelet coefficients derived from the MODWPT were statistically evaluated using the mean, standard deviation, energy, skewness, kurtosis, logarithmic energy entropy, max, min ...

Fluid–Rock Interactions And Its Implications On Eor: Critical Analysis, Experimental Techniques And Knowledge Gaps, Abubakar Isah, Muhammad Arif, Amjed Hassan, Mohamed Mahmoud, Stefan Iglauer

Research outputs 2022 to 2026

Characterization of fluid–rock interactions is essential for a broad range of subsurface applications such as understanding fluid flow in porous medium and enhanced oil recovery predictions. Enhanced oil recovery (EOR) is crucial in oil and gas production operations, it entails injecting fluids into the reservoir to enhance productivity. When fluids are injected, interactions occur between the injected fluids and the reservoir rock/fluids; and the outcomes of fluid–rock interactions critically impact the fluid flow in porous medium and the associated oil recovery. Furthermore, the associated changes in reservoir properties (porosity, permeability etc.) and flow behavior (i.e. wettability ...

Learning To Automate Follow-Up Question Generation Using Process Knowledge For Depression Triage On Reddit Posts, Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit Sheth

Publications

Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide informational or therapeutic services (e.g., cognitive behavioral therapy) to patients. However, the utility of CAs to assist in mental health triaging has not been explored in the existing work as it requires a controlled generation of follow-up questions (FQs), which are often initiated and guided by the mental health professionals (MHPs) in clinical settings. In the context of `depression', our experiments show that DLMs coupled with process knowledge in a mental health ...

Tailored Surface Textures To Increase Friction—A Review, Henara L. Costa, Jörg Schille, Andreas Rosenkranz

Friction

Surface textures with micro-scale feature dimensions still hold great potential to enhance the frictional performance of tribological systems. Apart from the ability of surface texturing to reduce friction, surface textures can also be used to intentionally increase friction in various applications that rely on friction for their adequate functioning. Therefore, this review aims at presenting the state-of-the-art regarding textured surfaces for high-friction purposes. After a brief general introduction, the recent trends and future paths in laser surface texturing are summarized. Then, the potential of surface textures to increase friction in different applications including adhesion, movement transmission and control, biomimetic applications ...

Role Of Nanoparticles In Achieving Macroscale Superlubricity Of Graphene/Nano-Sio2 Particle Composites, Panpan Li, Li Ji, Hongxuan Li, Lei Chen, Xiaohong Liu, Huidi Zhou, Jianmin Chen

Friction

Recent studies have reported that adding nanoparticles to graphene enables macroscale superlubricity to be achieved. This study focuses on the role of nanoparticles in achieving superlubricity. First, because graphene nanoscrolls can be formed with nanoparticles as seeds under shear force, the applied load (or shear force) is adjusted to manipulate the formation of graphene nanoscrolls and to reveal the relationship between graphene-nanoscroll formation and superlubricating performance. Second, the load-carrying role of spherical nano-SiO₂ particles during the friction process is verified by comparison with an elaborately designed fullerene that possesses a hollow-structured graphene nanoscroll. Results indicate that the incorporated nano-SiO ...

Optimization Of Pore Structure And Wet Tribological Properties Of Paper-Based Friction Materials Using Chemical Foaming Technology, Chang Li, Jie Fei, Enzhi Zhou, Rui Lu, Xiaohang Cai, Yewei Fu, Hejun Li

Friction

Paper-based friction materials are porous materials that exhibit anisotropy; they exhibit random pore sizes and quantities during their preparation, thereby rendering the control of their pore structure difficult. Composites with different pore structures are obtained by introducing chemical foaming technology during their preparation to regulate their pore structure and investigate the effect of pore structure on the properties of paper-based friction materials. The results indicate that the skeleton density, total pore area, average pore diameter, and porosity of the materials increase after chemical foaming treatment, showing a more open pore structure. The addition of an organic chemical foaming agent improves ...

Numerical Study On Butterfly Wings Around Inclusion Based On Damage Evolution And Semi-Analytical Method, Ye Zhou, Caichao Zhu, Xiaojin Chen, Wei Ye

Friction

Butterfly wings are closely related to the premature failure of rolling element bearings. In this study, butterfly formation is investigated using the developed semi-analytical three-dimensional (3D) contact model incorporating inclusion and material property degradation. The 3D elastic field introduced by inhomogeneous inclusion is solved by using numerical approaches, which include the equivalent inclusion method (EIM) and the conjugate gradient method (CGM). The accumulation of fatigue damage surrounding inclusions is described using continuum damage mechanics. The coupling between the development of the damaged zone and the stress field is considered. The effects of the inclusion properties on the contact status and ...