Results 71 to 80 of about 7,350 (305)
Adaptive tensor train learning algorithm based on single-aspect streaming model
Tongxin xuebao, 2023 An adaptive tensor train (TT) learning algorithm for the online decomposition problem of high-order tensors in single-aspect streaming model was investigated.Firstly, it was deduced that single-aspect streaming increment only changes the dimension of ...
Baoze MA +3 more
doaj +2 more sources
Resource-aware mining of data streams [PDF]
, 2005 Mining data streams has raised a number of research challenges for the data mining community. These challenges include the limitations of computational resources, especially because mining streams of data most likely be done on a mobile device with ...
Gaber, Mohamed Medhat +11 more
core +1 more source
Tumbling Magnetic Microrobots for Targeted In Vivo Drug Delivery in the GI Tract
Advanced Robotics Research, EarlyView.We introduce a microrobot design and integrated system for on‐demand targeted drug release in the gastrointestinal tract. The microrobot has an embedded magnet for actuation with external magnetic fields and is visualized in real time using ultrasound. It has two drug release ports sealed with a thermally sensitive wax. Local heating of the wax using a
Aaron C. Davis +7 more
wiley +1 more source
Predicting Coronavirus Pandemic in Real-Time Using Machine Learning and Big Data Streaming System
Complexity, 2020 Twitter is a virtual social network where people share their posts and opinions about the current situation, such as the coronavirus pandemic. It is considered the most significant streaming data source for machine learning research in terms of analysis,
Xiongwei Zhang +4 more
doaj +1 more source
Algorithms for Efficient, Compact Online Data Stream Curation
CoRRData stream algorithms tackle operations on high-volume sequences of read-once data items. Data stream scenarios include inherently real-time systems like sensor networks and financial markets. They also arise in purely-computational scenarios like ordered traversal of big data or long-running iterative simulations.
Matthew Andres Moreno +2 more
openaire +2 more sources
A Framework for Adversarially Robust Streaming Algorithms
, 2020 We investigate the adversarial robustness of streaming algorithms. In this context, an algorithm is considered robust if its performance guarantees hold even if the stream is chosen adaptively by an adversary that observes the outputs of the algorithm ...
Jayaram, Rajesh +7 more
core +1 more source
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Advanced Robotics Research, EarlyView.This work presents the MicroRoboScope, a highly integrated, compact, and portable microrobotic experimentation platform combining electromagnetic and acoustic actuation with real‐time visual feedback into a single, end‐to‐end device. The system enables closed‐loop control and tracking algorithm experimentation within an accessible and unified hardware ...
Max Sokolich +4 more
wiley +1 more source
Applied SciencesWith the evolution of cellular networks and wireless-local-area-network-based communication technologies, services for smart device users have appeared.
Jeonghun Woo +3 more
doaj +1 more source
New Algorithms and Lower Bounds for Streaming Tournaments [PDF]
We study fundamental directed graph (digraph) problems in the streaming model. An initial investigation by Chakrabarti, Ghosh, McGregor, and Vorotnikova [SODA'20] on streaming digraphs showed that while most of these problems are provably hard in general,
Kuchlous, Sahil, Ghosh, Prantar
core +1 more source