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Articles 61201 - 61230 of 1824559
Full-Text Articles in Entire DC Network
Mems 4110: Rapid Drink Chiller, Aidan F. Moriarty, John Babineau, Levi Gingerich, Quinn Close
Mems 4110: Rapid Drink Chiller, Aidan F. Moriarty, John Babineau, Levi Gingerich, Quinn Close
Mechanical Engineering Design Project Class
The purpose of this document is to outline the purpose and function of the rapid drink chiller device. This device is designed to replace traditional portable drink cooling methods, such as traditional styrofoam coolers, fridges, etc. Traditional methods require the transport and inclusion of ice, and require overly long cooling times, with the exception traditional fridges which are non-portable. The rapid drink chiller is designed to be light and compact in order to maximize transportability, accomplished via an all foam insulation construction around a waterproof box. The box is filled with a water-ethanol solution which is cooled to extremely low …
Mems 4110: Dbf Banner, Pachie Ackerman-Bennett, Joshua Paul Laue, Nazifa Younus
Mems 4110: Dbf Banner, Pachie Ackerman-Bennett, Joshua Paul Laue, Nazifa Younus
Mechanical Engineering Design Project Class
The DBFBanner is a project made for the WashU Design / Build / Fly club. After interviewing DBF club president Sarah Donner, we interpreted the club’s needs as: (1) a banner that could achieve vertical stability in flight; (2) the banner could deploy and release remotely; (3) the banner and associated components were as light as possible. We went through several design iterations, including mathematical and CAD models, mockups, prototypes, and testing apparatus. Many designs were considered, including designs based on linear motion and collapsible trusses. We arrived at a design that used a servo motor to rotate a 3D-printed …
Mems 4110: Precise Water Distribution System, Morelia R. Reyes-Perez, Jp Torack, Jakob Ayala
Mems 4110: Precise Water Distribution System, Morelia R. Reyes-Perez, Jp Torack, Jakob Ayala
Mechanical Engineering Design Project Class
This project focuses on designing and prototyping an automatic precise watering system to support plant research conducted in the Washington University greenhouse. The customer, graduate student Christina Youngpeter, needs a reliable method for delivering accurately measured water volumes to individual plants as part of a study on hydration effects. Manual watering can be time consuming, our system will provide a programmable, repeatable, and low maintenance solution.
Mems 4110: Asme Waste Collection Challenge, Leslie Alfaro, Cathy Zhao, Bari Diamond, Obike Anwisye
Mems 4110: Asme Waste Collection Challenge, Leslie Alfaro, Cathy Zhao, Bari Diamond, Obike Anwisye
Mechanical Engineering Design Project Class
For this project, our goal was to design and build a remote-controlled wastecollection robot that could pick up trash bins and deliver their contents to a dumpsite while staying within the strict rules of the ASME challenge. The robot had to fit inside a 50 cm cube, drive through six-inch lanes, follow traffic rules, and be fully controlled by a six-channel RC controller. These constraints shaped almost every decision we made throughout the design process.
Mems 4110: N1 Precise Water Distribution System, Lillian Salter, Ye Huang, Elaine Wang, Joy Luo
Mems 4110: N1 Precise Water Distribution System, Lillian Salter, Ye Huang, Elaine Wang, Joy Luo
Mechanical Engineering Design Project Class
The aim of the project is to construct a precise water distribution system for anthropology graduate student Christina Youngpeter, who is studying the impact of hydration levels on the growth of quinoa plants. As her experiment grows in scale, she increasingly needs a system that can measure and distribute water for her, saving hours otherwise spent meticulously measuring water for 36 plants and counting. The system must measure water accurately and distribute it to the plants cleanly and efficiently. It should also be scalable and autonomous, requiring minimal human intervention.
Mems 4110: The Egg Peeler, Susanna Yeh, Jessica Arnold, Peter Nesin, Finn Mcnamee
Mems 4110: The Egg Peeler, Susanna Yeh, Jessica Arnold, Peter Nesin, Finn Mcnamee
Mechanical Engineering Design Project Class
The purpose of this project is to assist the customer Neon Greens in accelerating their food preparation time by designing an egg peeler device. To have a better understanding of the customer needs and expectations, the design team participated in an interview with Neon Greens to address their vision and desires for this device. For the semester-long project, the team underwent various prototype stages, including the proof of concept, the initial prototype, and the final prototype. Our final design consists of a hopper that holds a batch of eggs on top and drops two eggs at a time, one on …
Mems 4110: Dbf Deployable Banner, Julia Peppe, Danny Bruns, Sarah Donner, Michael Safier
Mems 4110: Dbf Deployable Banner, Julia Peppe, Danny Bruns, Sarah Donner, Michael Safier
Mechanical Engineering Design Project Class
Create a device that stores a banner in an RC aircraft that can be remotely deployed to be towed and released upon command.
Mems 4110: Air Cannon Launcher Demo, Jackson Strauss, Avery Cohen, Wilson Gao, Jack Galloway
Mems 4110: Air Cannon Launcher Demo, Jackson Strauss, Avery Cohen, Wilson Gao, Jack Galloway
Mechanical Engineering Design Project Class
For our senior design class (MEMS 4110) at Washington University in St. Louis, we were tasked with creating a demonstration for the St. Louis Science Center that demonstrated an engineering principle or concept. The Science Center functions as a science-oriented museum and saw more than 600,000 visitors in 2024. For our demonstration, we wanted to showcase the principles of kinematic motion. Kinematic motion is study of the motion of objects without considering applied forces. Additionally, when the acceleration of an object is either zero or held constant, the trajectory path that the object follows can be described by a few …
Mems 4110: Trash-E (Terrain-Adaptive Remote Autonomous Sanitation Hauling Engineer), Jackson R. Weisbard, Raza Rabbani, Dhruv Goel, Kj Kernan
Mems 4110: Trash-E (Terrain-Adaptive Remote Autonomous Sanitation Hauling Engineer), Jackson R. Weisbard, Raza Rabbani, Dhruv Goel, Kj Kernan
Mechanical Engineering Design Project Class
The TRASH-E (Terrain-Adaptive Remote Autonomous Sanitation Hauling Engineer) project was created to compete in the 2025 ASME Student Design Challenge. For 2025, the ASME SDC asked for the development of a remotecontrolled robot that could collect and deposit trash from receptacles placed around a miniature city. The robot had to adhere to specific size and weight constraints, as well as obey traffic laws in the same manner as a real driver operating a motor vehicle.
Mems 4110: Parachute Snatch Force Tester, Adam Mallalieu, Ethan Riak, Jackson Shurman, Ryan Schmadtke
Mems 4110: Parachute Snatch Force Tester, Adam Mallalieu, Ethan Riak, Jackson Shurman, Ryan Schmadtke
Mechanical Engineering Design Project Class
This report discusses the design, development, and testing of a parachute snatch force tester for MEMS 411 Senior Design. The device is for the WURocketry Team, and aims to measure the peak force exerted on the rocket bulkhead during parachute ejection. This peak force is known as the snatch force, and is incredibly important when it comes to maintaining safety, improving performance, and material selection during the rocket’s production process. Current methods for testing and recording this snatch force are limited, so our team aimed to create a simple and cost effective solution. Our design utilizes a vertical support that …
Mems 4110: Arduino-Controlled Precise Water Distribution System, Jack M. Williams, Joe Sieracki, Nina Woodward
Mems 4110: Arduino-Controlled Precise Water Distribution System, Jack M. Williams, Joe Sieracki, Nina Woodward
Mechanical Engineering Design Project Class
Christina Youngepeter is a Graduate Student of Archaeology at Washington University in St. Louis. She is studying an ancient plant that fell out of use after 1400 CE, whose ideal watering conditions are lost to time. To better characterize the plant, Christina is running an experiment to determine the ideal watering conditions for plant development. This involves watering sets of the plant with different volumes of water twice a day. The different volumes of water received by the groups of plants are 933 mL, 833 mL, 733 mL, 617 mL, 517 mL, and 417 mL. The acceptable percent error in …
Mems 4110: Asme Garbage Collection Challenge, Johnny F. Malley Iii, Sam R. Waggoner, Kyler R. Kosanke, Oliver N. Stitt
Mems 4110: Asme Garbage Collection Challenge, Johnny F. Malley Iii, Sam R. Waggoner, Kyler R. Kosanke, Oliver N. Stitt
Mechanical Engineering Design Project Class
The AY25-26 ASME Student Design Competition (SDC) is inspired by the global issue of recycling and waste collection management. Garbage and recycling are, in many instances, collected at the curb or roadside, where residents and/or business establishments place their garbage and recyclables in designated containers for pickup by local waste management companies or municipalities. In some areas around the world, waste collection is a challenge to establish due to variations in terrains and storage locale/capacity. In some instances, waste management companies might utilize a single vehicle that separates materials during the collection process to minimize the number of required vehicles …
Mems 4110: Asme Waste Collection Challenge, Theo A. Mass, Grant Kaplan, Emanoeel Ghabrial, Joseph Gillett
Mems 4110: Asme Waste Collection Challenge, Theo A. Mass, Grant Kaplan, Emanoeel Ghabrial, Joseph Gillett
Mechanical Engineering Design Project Class
The Efficient Jolley Trash Grabber (EJTG) is a teleoperated vehicle adherent to the modified rules of the 2025-26 ASME Student Design Competition, hosted in MEMS 4110: Mechanical Engineering Design Project. The vehicle design was informed first by understanding the problem of waste collection. Patents, existing devices, user needs, and relevant codes and standards were reviewed to survey potential design approaches. The concept for the vehicle was generated by setting functionality, and brainstorming solutions to accomplish each goal. A mock-up vehicle was created using available materials, and four complete concepts were drawn each with a different design. Rigorous methods were used …
Mems 4110: Asme Waste Collection Challenge, Evelyn Madrigal, Letty Patino, Bing Ling, Michael Avaliani
Mems 4110: Asme Waste Collection Challenge, Evelyn Madrigal, Letty Patino, Bing Ling, Michael Avaliani
Mechanical Engineering Design Project Class
Make a remote-controlled vehicle that can traverse the course below (obeying traffic laws), collect garbage units from collection bins and deliver the garbage units to a receptacle.
Mems 4110: Egg Project, Rebecca Leighann Boone, Courtney Davis, Bebel Trani
Mems 4110: Egg Project, Rebecca Leighann Boone, Courtney Davis, Bebel Trani
Mechanical Engineering Design Project Class
Peeling hard-boiled eggs by hand is a time-consuming and tedious task that often results in dimples and cracks in the final product. Many chefs and home cooks have tried techniques, from boiling the eggs in baking soda to slipping off egg shells using a spoon, to perfect the peeling process. However, these attempts often fall short by either altering the taste of the egg or extending the amount of time and labor. In the restaurant business, having employees peel eggs for long periods of time is costly. The local St. Louis salad restaurant, Neon Greens, is selling a new protein-dense …
Mems 4110: Conservation Of Angular Momentum Demo, Matthew Brouillet, Iyanu Akinyemi, Mingxuan Bi, Matthew Gimbel
Mems 4110: Conservation Of Angular Momentum Demo, Matthew Brouillet, Iyanu Akinyemi, Mingxuan Bi, Matthew Gimbel
Mechanical Engineering Design Project Class
A demo was built to serve as a hands-on experience for reinforcing concepts behind the conservation of angular momentum.
Mems 4110: Precise Water Distribution System, Fadhimah Mohamed, Duyen Nguyen, Citlalli Sanchez-Ayala
Mems 4110: Precise Water Distribution System, Fadhimah Mohamed, Duyen Nguyen, Citlalli Sanchez-Ayala
Mechanical Engineering Design Project Class
Greenhouse research requires precise, repeatable watering to maintain consistent experimental conditions. As plant counts scale to 150–360 pots, manual watering becomes inefficient, inconsistent. This project aims to design an automated irrigation system that reliably delivers controlled water volumes to an initial set of 36 pots, operates under greenhouse conditions with minimal user intervention, and provides a scalable foundation for future expansion.
Mems 4110: Remotely Deployed Banner, Amiel Josiah Mari B. Silbol, Maxwell A. Fargo, Brant M. Weir, Elias Barro
Mems 4110: Remotely Deployed Banner, Amiel Josiah Mari B. Silbol, Maxwell A. Fargo, Brant M. Weir, Elias Barro
Mechanical Engineering Design Project Class
This project works in tangent with the Design, Build, Fly club at Washington University in St. Louis as one of the specific challenges required for the 2026 American Institute of Aeronautics and Astronautics' national competition. A banner must be stowed, deployed, and released during flight and must not interfere with the existing flight mechanics of the remote control aircraft.
Mems 4110: Soft Boiled Egg Peeler, Nina Fischer, Ruth Mellin, Jack Salamon, Malaya Hill
Mems 4110: Soft Boiled Egg Peeler, Nina Fischer, Ruth Mellin, Jack Salamon, Malaya Hill
Mechanical Engineering Design Project Class
This report outlines the design and evaluation of a hard-boiled egg–peeling device developed for the Saint Louis restaurant Neon Greens. The restaurant prepares an average of 150 soft-boiled eggs daily for dishes such as the Protein Salad. They requested a device able to autonomously peel 150 eggs per hour with minimal employee involvement.
Mems 4110: Air Hockey Table Physics Education Exhibit, Olaoluwa J. Adeniji, Salomon Dessalines, Gyvnn Mendenhall
Mems 4110: Air Hockey Table Physics Education Exhibit, Olaoluwa J. Adeniji, Salomon Dessalines, Gyvnn Mendenhall
Mechanical Engineering Design Project Class
This project centers on creating an educational air-hockey exhibit designed for use in a science museum. The goal of the device is to transform a familiar game into a hands-on demonstration of basic physics and engineering concepts such as motion, momentum, energy transfer, and impact forces. Through discussions with our customer, Professor Potter, we established that the exhibit must balance two priorities: it must be fun and intuitive for visitors of all ages, and it must provide meaningful real-time feedback that helps users understand the science behind the experience.
Mems 4110: Science Museum Bernoulli's Demo, Emma Sloan, Carter Hahnfeldt, Luke Mccann
Mems 4110: Science Museum Bernoulli's Demo, Emma Sloan, Carter Hahnfeldt, Luke Mccann
Mechanical Engineering Design Project Class
This report outlines the design and prototyping process of the Science Museum Bernoulli’s Demo (SMBD), a capstone project for MEMS 4110 Senior Design Project at Washington University in St. Louis. The SMBD is a fun game for a children’s science museum designed to demonstrate how the exit velocity of water from a pipe changes based on the pipe diameter. The design intends to teach kids about Bernoulli’s principle by allowing them to choose from two different sized pipes to spray water at a target. The key aspect of the game is that the water flows more slowly out of the …
Leads Data Insights: Affinity — Fall 2025, University Of North Dakota
Leads Data Insights: Affinity — Fall 2025, University Of North Dakota
LEADS Development Documents
Presentation of Fall 2025 data insights for the AFFINITY core value of UND LEADS. The slides summarize Activity Inventory and UND Today story coverage, compare Affinity progress between April 2025 and January 2026, and review outcome measures connected to belonging, workforce retention, first-year experience, athletics, global engagement, and military-affiliated students.
A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang
A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang
Research Collection School Of Computing and Information Systems
Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …
Filterfl: Knowledge Filtering-Based Data-Free Backdoor Defense For Federated Learning, Yanxin Yang, Ming Hu, Xiaofei Xie, Yue Cao, Pengyu Zhang, Yihao Huang, Mingsong Chen
Filterfl: Knowledge Filtering-Based Data-Free Backdoor Defense For Federated Learning, Yanxin Yang, Ming Hu, Xiaofei Xie, Yue Cao, Pengyu Zhang, Yihao Huang, Mingsong Chen
Research Collection School Of Computing and Information Systems
As a distributed machine learning paradigm, Federated Learning (FL) enables large-scale clients to collaboratively train a model without sharing their raw data. However, due to the lack of data auditing for untrusted clients, FL is vulnerable to poisoning attacks, especially backdoor attacks. By using poisoned data for local training or directly changing the model parameters, attackers can easily inject backdoors into the model, which can trigger the model to make misclassification of targeted patterns in images. To address these issues, we propose a novel data-free trigger-generation-based defense approach based on the two characteristics of backdoor attacks: i) triggers are learned …
Seeing 3d Through 2d Lenses: 3d Few-Shot Class-Incremental Learning Via Cross-Modal Geometric Rectification, Tuo Xiang, Xuemiao Xu, Bangzhen Liu, Jinyi Li, Yong Li, Shengfeng He
Seeing 3d Through 2d Lenses: 3d Few-Shot Class-Incremental Learning Via Cross-Modal Geometric Rectification, Tuo Xiang, Xuemiao Xu, Bangzhen Liu, Jinyi Li, Yong Li, Shengfeng He
Research Collection School Of Computing and Information Systems
The rapid growth of 3D digital content necessitates expandable recognition systems for open-world scenarios. However, existing 3D class-incremental learning methods struggle under extreme data scarcity due to geometric misalignment and texture bias. While recent approaches integrate 3D data with 2D foundation models (e.g., CLIP), they suffer from semantic blurring caused by texture-biased projections and indiscriminate fusion of geometric-textural cues, leading to unstable decision prototypes and catastrophic forgetting. To address these issues, we propose Cross-Modal Geometric Rectification (CMGR), a framework that enhances 3D geometric fidelity by leveraging CLIP’s hierarchical spatial semantics. Specifically, we introduce a Structure-Aware Geometric Rectification module that hierarchically …
Omnivton: Training-Free Universal Virtual Try-On, Zhaotong Yang, Yuhui Li, Shengfeng He, Xinzhe Li, Yangyang Xu, Junyu Dong, Yong Du
Omnivton: Training-Free Universal Virtual Try-On, Zhaotong Yang, Yuhui Li, Shengfeng He, Xinzhe Li, Yangyang Xu, Junyu Dong, Yong Du
Research Collection School Of Computing and Information Systems
Image-based Virtual Try-On (VTON) techniques rely on either supervised in-shop approaches, which ensure high fidelity but struggle with cross-domain generalization, or unsupervised in-the-wild methods, which improve adaptability but remain constrained by data biases and limited universality. A unified, training-free solution that works across both scenarios remains an open challenge. We propose OmniVTON, the first training-free universal VTON framework that decouples garment and pose conditioning to achieve both texture fidelity and pose consistency across diverse settings. To preserve garment details, we introduce a garment prior generation mechanism that aligns clothing with the body, followed by continuous boundary stitching technique to achieve …
Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang
Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang
Research Collection School Of Computing and Information Systems
Traditional ship detection methods primarily rely on single-modal approaches, such as visible or infrared images, which limit their application in complex scenarios involving varying lighting conditions and heavy fog. To address this issue, we explore the advantages of short-wave infrared (SWIR) and long-wave infrared (LWIR) in ship detection and propose a novel single-stage image fusion detection algorithm called LSFDNet. This algorithm leverages feature interaction between the image fusion and object detection subtask networks, achieving remarkable detection performance and generating visually impressive fused images. To further improve the saliency of objects in the fused images and improve the performance of the …
Parameter-Efficient Variational Autoencoder For Multimodal Multi-Interest Recommendation, Nhu Thuat Tran, Hady Wirawan Lauw
Parameter-Efficient Variational Autoencoder For Multimodal Multi-Interest Recommendation, Nhu Thuat Tran, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Learning user preferences in recommendation systems is enriched by multimodal features, such as textual and visual content, and amplified by multi-interest modeling with Variational AutoEncoders (VAEs). However, prior efforts are limited by single modality focus and cumbersome, parameter-heavy architecture designs. To address these limitations, we introduce an innovative solution that blends the semantic richness of multimodal data with the representational power of multi-representation VAEs. Drawing inspiration from Mixture of Experts (MoE), we cast each VAE as an expert tailored to a specific modality, then fuse them via a novel parameter-merging function into a lean, unified model. This approach efficiently captures …
Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration, Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang
Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration, Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang
Research Collection School Of Computing and Information Systems
Deep reinforcement learning (DRL) has emerged as an effective technique for dynamic algorithm configuration, particularly in evolutionary computation, enabling adaptive parameter updates during algorithmic execution. DRL-based methods have shown broad applicability across different problem domains and are designed to configure algorithms without problem-specific information, making them highly transferable across problem variants and scalable to different problem sizes. This paper proposes a novel graph neural network-based approach that learns representations of Search Trajectory Networks (STNs) to track the convergence behavior of multiple objectives and dynamically reconfigures multiobjective evolutionary algorithms during execution. By capturing how solutions evolve and interact over time, the …
Mitigating Cross-Modal Representation Bias For Multicultural Image-To-Recipe Retrieval, Qing Wang, Chong-Wah Ngo, Yu Cao, Ee-Peng Lim
Mitigating Cross-Modal Representation Bias For Multicultural Image-To-Recipe Retrieval, Qing Wang, Chong-Wah Ngo, Yu Cao, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Existing approaches for image-to-recipe retrieval have the implicit assumption that a food image can fully capture the details textually documented in its recipe. However, a food image only reflects the visual outcome of a cooked dish and not the underlying cooking process. Consequently, learning cross-modal representations to bridge the modality gap between images and recipes tends to ignore subtle, recipe-specific details that are not visually apparent but are crucial for recipe retrieval. Specifically, the representations are biased to capture the dominant visual elements, resulting in difficulty in ranking similar recipes with subtle differences in use of ingredients and cooking methods. …