Tootfinder

Author Once, Publish Everywhere: Portable Metadata Authoring with the CEDAR Embeddable Editor
Martin J. O'Connor, Marcos Martinez-Romero, Attila L. Egyedi, Mete U. Akdogan, Michael V. Dorf, Mark A. Musen
https://arxiv.org/abs/2508.00859

Author Once, Publish Everywhere: Portable Metadata Authoring with the CEDAR Embeddable Editor
High-quality, "rich" metadata are essential for making research data findable, interoperable, and reusable. The Center for Expanded Data Annotation and Retrieval (CEDAR) has long addressed this need by providing tools to design machine-actionable metadata templates that encode community standards in a computable form. To make these capabilities more accessible within real-world research workflows, we have developed the CEDAR Embeddable Editor (CEE)-a lightweight, interoperable Web Component tha…

Exploiting complex 3D-printed surface structures for portable quantum technologies
Nathan Cooper, David Johnson, Benjamin Hopton, Matthew Overton, David Stupple, Alexandra Bratu, Edward Wilson, John Robinson, Laurence Coles, Manolis Papastavrou, Lucia Hackermueller
https://arxiv.org/abs/2507.01476

Exploiting complex 3D-printed surface structures for portable quantum technologies
Portable quantum technologies require robust, lightweight apparatus with superior performance. For techniques dependent upon high-vacuum environments, such as atom interferometers and atomic clocks, 3D-printing enables new avenues to tailor in-vacuum gas propagation dynamics. We demonstrate intricate, fine-scale surface patterning of 3D-printed vacuum components to increase the rate at which gas particles collide with the surface. By applying a non-evaporable getter coating for use as a surface…

I got myself a portable solar panel, which I can use while camping and at home for charging power banks. I’m very impressed with how well it works, even on a cloudy day! The purpose of the panel is basically to power my power banks so I have green energy to charge my phone, tablet, headphones, USB lights, and electric toothbrush. It’s not much, but every bit helps to keep the bill lower.
#PortableSolarPanel

Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper
Xinyue Zhu, Binghao Huang, Yunzhu Li
https://arxiv.org/abs/2507.15062

Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper
Handheld grippers are increasingly used to collect human demonstrations due to their ease of deployment and versatility. However, most existing designs lack tactile sensing, despite the critical role of tactile feedback in precise manipulation. We present a portable, lightweight gripper with integrated tactile sensors that enables synchronized collection of visual and tactile data in diverse, real-world, and in-the-wild settings. Building on this hardware, we propose a cross-modal representatio…

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimization
Benjamin Coriat, Eric Benhamou
https://arxiv.org/abs/2507.18560

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimization
This paper presents a novel hierarchical framework for portfolio optimization, integrating lightweight Large Language Models (LLMs) with Deep Reinforcement Learning (DRL) to combine sentiment signals from financial news with traditional market indicators. Our three-tier architecture employs base RL agents to process hybrid data, meta-agents to aggregate their decisions, and a super-agent to merge decisions based on market data and sentiment analysis. Evaluated on data from 2018 to 2024, after t…

I'm making my SmartHome dumb again.
I got rid of my Google Assistants, smart lights, and plugs, and switched to LED bulbs to save energy. On top of this, I got a portable solar panel to charge my small devices.
For the evening, I now have a USB rechargeable LED light.
I’m doing this to reduce the cost of my electricity bill. Plus, it’s a good way to get rid of big tech products.
#SmartHome

RIMMS: Runtime Integrated Memory Management System for Heterogeneous Computing
Serhan Gener, Aditya Ukarande, Shilpa Mysore Srinivasa Murthy, Sahil Hassan, Joshua Mack, Chaitali Chakrabarti, Umit Ogras, Ali Akoglu
https://arxiv.org/abs/2507.20514

RIMMS: Runtime Integrated Memory Management System for Heterogeneous Computing
Efficient memory management in heterogeneous systems is increasingly challenging due to diverse compute architectures (e.g., CPU, GPU, FPGA) and dynamic task mappings not known at compile time. Existing approaches often require programmers to manage data placement and transfers explicitly, or assume static mappings that limit portability and scalability. This paper introduces RIMMS (Runtime Integrated Memory Management System), a lightweight, runtime-managed, hardware-agnostic memory abstractio…

Design and Implementation of a Lightweight Object Detection System for Resource-Constrained Edge Environments
Jiyue Jiang, Mingtong Chen, Zhengbao Yang
https://arxiv.org/abs/2507.16155

Design and Implementation of a Lightweight Object Detection System for Resource-Constrained Edge Environments
This project aims to develop a system to run the object detection model under low power consumption conditions. The detection scene is set as an outdoor traveling scene, and the detection categories include people and vehicles. In this system, users data does not need to be uploaded to the cloud, which is suitable for use in environments with portable needs and strict requirements for data privacy. The MCU device used in this system is STM32H7, which has better performance among low power devic…

EdgeSRIE: A hybrid deep learning framework for real-time speckle reduction and image enhancement on portable ultrasound systems
Hyunwoo Cho, Jongsoo Lee, Jinbum Kang, Yangmo Yoo
https://arxiv.org/abs/2507.03937

EdgeSRIE: A hybrid deep learning framework for real-time speckle reduction and image enhancement on portable ultrasound systems
Speckle patterns in ultrasound images often obscure anatomical details, leading to diagnostic uncertainty. Recently, various deep learning (DL)-based techniques have been introduced to effectively suppress speckle; however, their high computational costs pose challenges for low-resource devices, such as portable ultrasound systems. To address this issue, EdgeSRIE, which is a lightweight hybrid DL framework for real-time speckle reduction and image enhancement in portable ultrasound imaging, is …

Evaluating Ensemble and Deep Learning Models for Static Malware Detection with Dimensionality Reduction Using the EMBER Dataset
Md Min-Ha-Zul Abedin, Tazqia Mehrub
https://arxiv.org/abs/2507.16952

Evaluating Ensemble and Deep Learning Models for Static Malware Detection with Dimensionality Reduction Using the EMBER Dataset
This study investigates the effectiveness of several machine learning algorithms for static malware detection using the EMBER dataset, which contains feature representations of Portable Executable (PE) files. We evaluate eight classification models: LightGBM, XGBoost, CatBoost, Random Forest, Extra Trees, HistGradientBoosting, k-Nearest Neighbors (KNN), and TabNet, under three preprocessing settings: original feature space, Principal Component Analysis (PCA), and Linear Discriminant Analysis (L…