Engineering Commons^™

A Method For Predicting Fractures In Carbonate Reservoirs Based On Fracture Identification-Sensitive Log-Seismic Parameter Model, Wang Zhiwei, Zhang Kai, Wu Qunhu, Zhang Benhua, Yu Shina, Zhang Zunxiang, Wu Yanjia

Coal Geology & Exploration

Carbonate reservoirs show fractures and strong heterogeneity, leading to limited applications of a single logging or seismic method in fracture identification. Therefore, this study proposed a method for predicting fractures in carbonate reservoirs based on a fracture identification-sensitive log-seismic parameter (FISLSP) model, and the details are as follows: (1) Based on petrophysical analysis results, as well as formation micro-imaging (FMI) logs and the interpretations of fractures at well locations, this study established a segmental fracture identification-sensitive parameter (FISP) model for fractures at well locations; (2) Using the optimal seismic attributes of near-well seismic traces determined based on the high-quality fractured …

Application And Prospect Of Acoustic Detection In The Mining Sector, Deng Jun, Wang Jinrui, Ren Shuaijing, He Qian, Wang Caiping, Qu Gaoyang

Coal Geology & Exploration

Acoustic detection for mines is a geophysical prospecting technique for mine information detection based on acoustic methods. Compared with other detection methods, acoustic detection has the advantages of wide applicability, high reliability, and low economic investment. This paper reviews the development of acoustic detection technology in the mine field and sorts out and expounds on the research progress and technical characteristics of this technology in detecting basic physical information inside mines and geological information outside mines. Furthermore, this study investigates the detection mechanisms, implementation methods, and applicable scenarios of this technology in determining the object states in the field of …

Study On Modification Of Plant Gum Flushing Fluid In Coal-Bearing Strata And Its Mechanism, Xie Chengchao, Wang Sheng, Yan Peng, Chen Liyi, Li Bingle, Zhang Jie

Coal Geology & Exploration

To improve the adverse effects of the depletion of plant gum resources on the application of flushing fluid in complex strata such as coal-bearing strata, a study was conducted on the compound and crosslinking modification of guar gum. A new type of plant gum flushing fluid (GXB) was developed using xanthan gum as the compound synergist and organic boron as the crosslinking modifier, with cross-linking control agent and inorganic treatment agent as the supplementary. Meanwhile, a series of performance evaluation was carried out. The evaluation results show that GXB has excellent performance and can meet the requirements of drilling in …

Effects Of Increasing Sintering Pressure On The Performance Of Impregnated Diamond Bit, Yang Zhan, Tan Songcheng, Fang Xiaohong, Yang Kaihua

Coal Geology & Exploration

The matrix formulas of conventional hot-pressed impregnated diamond bits are mostly elemental metal systems, using WC or YG8 as the skeleton materials, Cu alloys as the bonding materials, and Ni, Co, Fe and Mn as the intermediate materials. Due to the compositions and contents of the bonding and skeleton materials in the formulas, the suitable sintering pressure is limited (≤16 MPa), while the sintering temperature is relatively high (≥ 930℃), resulting in a lower relative ratio of the actual and theoretical densities (≤98%) for the diamond bit matrix. However, the high sintering temperature will cause thermal damage to the diamonds, …

Introducing Ros-Projects To Undergraduate Robotic Curriculum, Lili Ma, Yu Wang, Chen Xu, Xiaohai Li

Publications and Research

This paper describes three MATLAB-ROS-based simulation projects developed for an undergraduate robotics course. The Robot Operating System (ROS) is an open-source framework that helps researchers and developers build and reuse code between robotics applications. Adoption of ROS in the undergraduate curricula is still rare due to its demanding requirements of C++/Python/Java programming skills and familiarity with Linux. Recently, MathWorks released its ROS Toolbox, making it easier to interact with simulators like the Gazebo and ROS-supported physical robots. The MATLAB-ROS-Gazebo simulation platform allows students to utilize other MATLAB Toolboxes, such as Image Processing, Computer Vision, Visualization, and Navigation Toolboxes, for fast …

Impact Of Perceived Stress During Oral Examination On Student Performance Outcomes, Alex M. Phan, Minju Kim, Marko V. Lubarda, Curt Schurgers, Huihui Qi

Psychology Faculty Articles and Research

Perceived stress plays an important role in student performance during examinations. There has been substantial research on how examinations impact students' emotional experiences in diverse academic contexts in connection to validity, reliability, and equity of assessment. The potential of some exams to produce increased anxiety in a portion of students has been recognized as a serious threat to these three assessment attributes. In light of this, the need for further studies on the impact of perceived stress on student performance is critical with the recent rise in interest in oral examinations as an assessment tool for large undergraduate courses. This …

From Rote Learning To Deep Learning: Filling The Gap By Enhancing Engineering Students' Reasoning Skills Through Explanatory Learning Activities, Huihui Qi, Minju Kim, Yu Li, Carolyn L. Sandoval, Curt Schurgers, Marko Lubarda, Xuan Emily Gedney, Saharnaz Baghdadchi, Alex M. Phan

Psychology Faculty Articles and Research

Rote learning refers to the superficial learning of concepts and procedures, typically by brute memorization and with little integration into existing cognitive schemas, resulting in poor knowledge retention and inability to apply the knowledge in new and evolving contexts. With rote learning, students usually learn declarative and procedural knowledge but usually do not pay attention to conditional knowledge (when to use what knowledge). As a result, they usually can replicate the problem-solving process in a familiar context but are unable to transfer the knowledge and use the concept for a new application.

This paper explores the use of explanatory learning …

Peer Oral Exams: A Learner-Centered Authentic Assessment Approach Scalable To Large Classes, Marko V. Lubarda, Alex M. Phan, Maziar Ghazinejad, Nathan Delson, Saharnaz Baghdadchi, Curt Schurgers, Minju Kim, Josephine Relaford-Doyle, Carolyn L. Sandoval, Huihui Qi

Psychology Faculty Articles and Research

Peer oral exams, a cross between oral exams and peer assessment, were designed and implemented in a high-enrollment undergraduate computer programming course for engineers. The intention was to leverage the educational and implementational advantages of both evidence-based approaches simultaneously. Oral exams, for instance, have been argued to promote conceptual understanding, self-reflection, communication competency, and professional identity formation in students – but their deployment in large classes is resource-demanding and nontrivial, stifling their broader adoption. Peer assessment, on the other hand, is highly scalable and affords students many potential educational benefits of its own, including the benefits of peer-enhanced learning, more …

Development Of A Raspberry Pi-Controlled Vex Robot For A Robotics Technology Course, Lili Ma, Justin Bartholomew, Yu Wang, Xiaohai Li

Publications and Research

This paper describes the development of a Raspberry PI-controlled VEX robot for an undergraduate robotic course. The Raspberry PI controls the mobile base built using the VEX robotics kit without using the Cortex micro-controller that comes with the kit. The aim is to create a physical robot that is manageable, easily replicable, and capable of performing advanced robotic control tasks such as vision-based control.

The constructed robot adopts the great features of the PI and the VEX hardware. Firstly, the VEX hardware consists of various sensors and actuators for students to practice the construction and assembly of an autonomous robot. …

Advances In Multiagent Systems Control: Multiplex Information Networks-Based Approaches And Beyond, Kimberly Witke

USF Tampa Graduate Theses and Dissertations

Multiagent systems control designs offer numerous advantages to increasingly complex civilian, military, and scientific tasks ranging from intelligent satellite swarm controls or autonomous traffic controls to remote triage and repair or remote wildlife observation, where the performance of a single agent is insufficient to execute the task at hand. Traditional methods in multiagent systems controls, however, have been infeasible for use in scalable, large-group formation controls.

With this in mind, the contribution of this dissertation is to bridge the gap in knowledge through both theoretical and experimental validation of multiagent systems control architectures. It addresses the challenges presented by unreliable, …

Work In Progress: Assessing Engineering Students' Behavioral Engagement And Learning; Survey Development And Validation, Ibukun Samuel Osunbunmi, Kurt Henry Becker, Young Min Kim, Mohammad Al Mestiraihi

Electrical and Computer Engineering Faculty Publications

Studies have shown that the more involved students are with their learning, the better their achieved desired educational outcome. However, little is known about the extent to which the existing engineering curriculum and pedagogical strategy implemented elicit engineering students’ engagement in the Middle East and North Africa region (MENA) of the world. The goal of this study is to examine to what extent the existing engineering curriculum elicits student engagement in self-learning and collaborative learning. This effort is part of the ongoing re-evaluation and redesign of the water engineering curriculum of one of the countries in the MENA region by …

Uav-Based Quantification Of Dynamic Lahar Channel Morphology At Volcán De Fuego, Guatemala, Jerry C. Mock, Jeffrey B. Johnson, Armando Pineda, Gustavo Bejar, Amilcar Roca

Michigan Tech Publications

This study quantified erosional and depositional processes for secondary lahars in Las Lajas drainage at Volcán de Fuego, Guatemala, during the rainy season from May to October 2021. Abundant pyroclastic material from ongoing eruptive activity is remobilized seasonally during heavy precipitation, which can impact infrastructure and populations living near Fuego. Our region of focus was in an agricultural zone 6 to 10 km from the summit, surveyed with an unoccupied aerial vehicle (UAV) quadcopter at monthly intervals. Imagery was processed into overlapping time-lapse structure from motion digital elevation models (DEMs). DEMs were differenced to find volumetric changes as a function …

Impact Of Critical Narrative On Students’ Abilities To Recognize Ethical Dilemmas In Engineering Work, Jeff Brown, Chad Rohrbacher, Taylor J. Mitchell, Dr. Leroy Long Iii, Jenna Korentsides, Joseph R. Keebler

Publications

This study aims to investigate the impact of exposure to critical narratives on students' abilities to recognize ethical dilemmas and broader impacts in engineering work. Critical narratives are place-based stories that engage students and help them enhance their critical thinking skills by making connections between the narratives, broader impacts of engineering work, and their responsibility to address these issues. The effectiveness of the critical narrative intervention was assessed by implementing discussion-based assignments around three critical narratives, which required students to listen to the narrative, respond to focus questions, engage with their peers, and reflect on the process. The intervention was …

Deep Learning Enhancement And Privacy-Preserving Deep Learning: A Data-Centric Approach, Hung S. Nguyen

USF Tampa Graduate Theses and Dissertations

Deep Learning and its applications have become attractive to a lot of research recentlybecause of its capability to capture important information from large amounts of data. While most of the work focuses on finding the best model parameters, improving machine learning performance from data perspective still needs more attention. In this work, we propose techniques to enhance the robustness of deep learning classification by tackling data issue. Specifically, our data processing proposals aim to alleviate the impacts of class-imbalanced data and non- IID data in deep learning classification and federated learning scenarios. In addition, data pre-processing strategies such that dimensionality …

Toward Architecture For Discrete Event Logistics Systems Design, Leon Mcginnis

International Material Handling Research Colloquium

No abstract provided.

Transportation Service Provider Collaboration: Benefits And Insights, Steven Roesch, Kimberly Ellis

International Material Handling Research Colloquium

No abstract provided.

Optimization Of Cargo Handling Equipment At The Airport, David Šourek

International Material Handling Research Colloquium

No abstract provided.

On Logistics And Motion Planning – An Informal Axiomatic Approach, Moritz Roidl

International Material Handling Research Colloquium

No abstract provided.

Handling Disruptions In A Network With Cross-Docking, Vishal Badyal, Fahim Ahmed, Nikhil Aditya Eti, Nathan Huynh, William Ferrell

International Material Handling Research Colloquium

No abstract provided.

Supply Chain Disruptors And Their Impact On The Future Of Manufacturing, Logistics, And Distribution, Henk M. Zijm, Sunderesh S. Heragu

International Material Handling Research Colloquium

No abstract provided.

Breakout Session E-2: "Information", Jelmer Pier Van Der Gaast, Moritz Roidl

International Material Handling Research Colloquium

No abstract provided.

Breakout Session E-3: "The Ideal Gtp Characteristics", Russell D. Meller, Uday Venkatadri

International Material Handling Research Colloquium

No abstract provided.

Breakout Session E-1: "Resilience", Fabio Sgarbossa, William Ferrell

International Material Handling Research Colloquium

No abstract provided.

Breakout Session D-3: "Robotics", Jennifer Pazour, Moritz Roidl

International Material Handling Research Colloquium

No abstract provided.

Breakout Session D-1: "Sustainability", Uday Venkatadri, Kimberly Ellis

International Material Handling Research Colloquium

No abstract provided.

Breakout Session D-2: "Artificial Intelligence", Sunderesh S. Heragu, Hector J. Carlo

International Material Handling Research Colloquium

No abstract provided.

A Fluid Flow Queuing Network Model For Performance Analysis Of Bulk Liquid Terminals, Debjit Roy, Werner Scheinhardt, Jan-Kees Van Ommeren

International Material Handling Research Colloquium

No abstract provided.

Decision Rules For The Robotic Mobile Fulfillment System Of A Pcb Assembly Factory Warehouse, Ching-Jung Ting, Hendra Permana, Hsien-Mi Meng

International Material Handling Research Colloquium

No abstract provided.

Requirements For Generating Learning Environments For Autonomous Systems Behavior In A Digital Continuum, Anike Murrenhoff

International Material Handling Research Colloquium

No abstract provided.

Evaluating Business Service Models For On-Demand Warehousing: A Double Perspective On Suppliers And Customers, Maria Grazia Gnoni, Fabiana Tornese

International Material Handling Research Colloquium

No abstract provided.