Ludim Guerrero的动态

https://lnkd.in/eXmUkQTs Thank you for all your kind words concerning my machinery reliability examples. Please consider getting my book, filled with dozens of examples including chapters dedicated to electric discharge machining damage and rotor dynamics as it applies to avoiding rigid body modes during motor testing.

I am excited to share that our paper, titled "????????-???????? ???????? ?????????????????? ?????? ?????????????? ???????? ???????????????? ?????????? ?????????? ?????????????? ???????????????????? ???? ??????-???????????? ????????????," has been accepted for presentation at the????????? ???????????????????? ???? ?????????????? ?????????????? ?????? 3?? ???????? ???????????????????? (???????? ????), which will be held in Saint-Malo, France. This work will be presented as part of?IEEE VR's 4th International Workshop on eXtended Reality for Industrial and Occupational Supports (XRIOS). We propose a novel framework that uses 360-degree video recordings, human posture estimation, and Gaussian Splatting for real-time digital twin modeling. Applications of this approach extend to industrial safety, ergonomics, and training, providing scalable and human-centered solutions. This paper is part of the ongoing research at the HiMER Lab in the field of digital twin modeling. We'll have more to share soon! A big thank you to my doctoral advisor and co-author for this work, Dr. Heejin Jeong, and our collaborating author, Dr. Ricardo Eiris. We gratefully acknowledge funding support from the Pilot Project Research Training Program at Southern California NIOSH Education and Research Center (SCERC).

"Cool, cool, cool, cool, cool" One year in the World of Hardware Electronics! ?? This month marks my one-year anniversary at Schneider Electric, and what a ride it has been! From deciphering schematics to tackling stubborn components, I've truly embraced the art of turning "what does this do?" into "I can help fix that!" Reflecting on my first year, here are some key highlights: ?? Rookie Moments: I began my work eager to impress, only to find myself connecting the wrong wires during my early days of debugging. Let's just say the board got a bit more toasted than bread! ?? ??Teamwork makes the dream work: I've learned that collaboration is key - especially when troubleshooting a project that feels like it's taken a life of it's own! (also when the team brings snacks/chocolates ??) ??Learning curve: I went from "Is this a resistor or a capacitor?" to confidently discussing voltage drops and signal integrity. (Oh yes, also learnt that snacks tend to disappear by 10.45am??) A heartfelt thank you to my amazing team for their support and guidance. Here's to another year of innovation, learning and hopefully fewer "oops" moments! ??

Thanks for watching our channel over the years! We love helping folks on their journey to become professional engineers! Have we helped you? Let us know below! #peexam #feexam #civilengineeringacademy #civilengineering

I'm excited to share that my recent research paper, "Enhancing Exercise Efficacy: A Predictive EMG Analysis for Dumbbell Press Workouts," has been published at the International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)! In collaboration with Shreya Chaurasia and under the guidance of Dr Sujatha R Upadhyaya, and Dr Ramesh Debur, our study presents a machine learning-based EMG model designed to optimize dumbbell press workouts by identifying optimal and marginal repetitions in real-time. By analyzing EMG data from the pectoral and deltoid muscles, our model provides dynamic feedback on load, rest, and technique, helping improve workout quality and safety. With models like ANN, Random Forest, Logistic Regression, and LSTM, we observed high classification accuracy in exercise quality assessment, which could greatly benefit strength and conditioning programs. The paper can be found here: https://lnkd.in/eExmxVW2 Thank you to everyone involved, and I look forward to exploring further applications in sports performance optimization!

Cohda's MK6 can provide lane-accurate C-ITS warnings. We tested several use cases with a C-ITS enabled motorcycle and car on Toyota's test facility in Altona. We tested two lane-sensitive use cases: forward collision and blind spot detection. In variations of these use cases (same lane, different lane) C-ITS delivered appropriate warnings. More testing to be done, but the initial performance was good. In the coming months we will prepare for end-user testing of the same and other use cases. Thank you for your support: Harsh Trivedi (FIEAust CPEng NER RPEQ) Blake Harris Julian O'Loughlin Ian Christensen Lee-Ann Breger Renae Leeson Ada I. Lin Paul Gray iMOVE Australia Centre for Technology Infusion La Trobe University Toyota Motor Corporation Australia

Thank you all for the overwhelming response and inquiries! Many of you have asked about the current challenges that data-driven solutions can address. Instead of replying individually, I'd like to share some key problems we believe data can significantly impact.?I will share more details as we progress in a separate blog article. Industry: Pharma/FMCG/AgroChemical/Apparel Problem: Counterfeiting is a major issue, with reports indicating that 20-25% of the market in these industries in India consists of counterfeit products. We are currently evaluating this problem specifically for the Pharma industry. Stay tuned for more insights on my LinkedIn page. Industry: Automotive Problem: With cars becoming more reliable and the rise of electric vehicles (EVs), revenue from service businesses is expected to decline. This challenge can be addressed by either increasing car prices or creating new revenue streams through mobility solutions, data-led services, and more. Thank you for your interest and support. I look forward to sharing more updates as soon as we define new revenues from these two data sources.

Batteries plays an important role in the green transition, and we are very well under ways with advanced modelling which can guide the industry and de-risk the investments. Equally important to the performance and safety of the batteries is the development and reuse of battery materials. In Resovlent, we are right now scouting for the right project to engage in on these matters. I am always happy to meet and talk about opportunities for collaboration ?? #greentransition #batteries #lifecycle #SDG #resolvent #multiphysics

Hello everyone, I am thrilled to share the progress on our final year project. After some setbacks and modifications, we have successfully implemented AMCL (Adaptive Monte Carlo Localization) on our simulated robot. While this is a significant milestone, there are still many more functionalities to be added. Our goal is to build a safeguarding robot for the streets. Since our team is new to ROS2, we are unable to find out a way for implementing localization in outdoor environments and inter-city navigation. In our previous post, we mentioned an issue with the simulation, and we're grateful to the ROS community specialists who reached out to help us resolve those problems. Your support has been invaluable! As Gazebo Classic has reached its end of life, we attempted to migrate to Ignition Gazebo, which led to a previous issue — the robot was unable to turn along the z-axis unexpectedly. Unfortunately, despite our efforts, we were unable to resolve this issue and decided to continue using Gazebo Classic. If anyone has any suggestions or ideas on how to address these challenges, we would be grateful for your input. Thank you all for your wonderful support! Team members Radhika Kurva NAGARAJA MOTHUKURI Kotha Jyothireddy Sai Shiva Ram Peddireddy

?? Today is the advisory board meeting of the Fraunhofer lighthouse project Neurosmart at our institute. We're working in this project to make sensors learn to think ??. ? Why? Autonomous robots ?? are packed with sensors and electronics to perceive their environment. This causes high energy consumption ?. So we're developing an energy-efficient neuromorphic in-memory accelerator which is tailored to the respective sensor. The human brain serves as a model ??. ?? What does Fraunhofer IPMS do in the project? We train the circuitry of the neuromorphic accelerator. For the internal control of the data flows, we use our RISC-V processor core EMSA5 ??. Furthermore, we are involved in the research of the neural network model for data evaluation. The goal here is the automated mapping on the available hardware topology as well as its transfer to a circuit design ??. The communication between pre-processing (FPGA) and accelerator circuitry takes place via a real-time capable high-speed Ethernet interface ??. ?? A big thank you to our project partners: Fraunhofer ISIT - Fraunhofer IAIS - Fraunhofer IWU - Fraunhofer-Institut für Mikroelektronische Schaltungen und Systeme IMS