Tootfinder

Flexible MIMO for Future Wireless Communications: Which Flexibilities are Possible?
Zhe Wang, Jiayi Zhang, Bokai Xu, Wenhui Yi, Emil Bj\"ornson, Bo Ai
https://arxiv.org/abs/2506.07599

Flexible MIMO for Future Wireless Communications: Which Flexibilities are Possible?
To enable next-generation wireless communication networks with modest spectrum availability, multiple-input multiple-output (MIMO) technology needs to undergo further evolution. In this paper, we introduce a promising next-generation wireless communication concept: flexible MIMO technology. This technology represents a MIMO technology with flexible physical configurations and integrated applications. We categorize twelve representative flexible MIMO technologies into three major classifications…

heise | Goodbye Chrome: Warum Vivaldi der bessere Browser ist
Vivaldi ist eine clevere Chrome-Alternative: Der Browser bietet viele Funktionen und lässt sich flexibel anpassen. Und Werbe-Tracker blockiert er auch noch.

Deep Reinforcement Learning-Based Motion Planning and PDE Control for Flexible Manipulators
Amir Hossein Barjini, Seyed Adel Alizadeh Kolagar, Sadeq Yaqubi, Jouni Mattila
https://arxiv.org/abs/2506.08639

Deep Reinforcement Learning-Based Motion Planning and PDE Control for Flexible Manipulators
This article presents a motion planning and control framework for flexible robotic manipulators, integrating deep reinforcement learning (DRL) with a nonlinear partial differential equation (PDE) controller. Unlike conventional approaches that focus solely on control, we demonstrate that the desired trajectory significantly influences endpoint vibrations. To address this, a DRL motion planner, trained using the soft actor-critic (SAC) algorithm, generates optimized trajectories that inherently …

I'm incredibly proud to report that Pryce Millikin, the current master's student in my lab, has been recognized with an Honorable Mention in this year's NSF Graduate Research Fellowship competition, in a year when NSF gave out just 1,000 GRF awards across every field of science nationwide

Future Deployment and Flexibility of Distributed Energy Resources in the Distribution Grids of Switzerland
Lorenzo Zapparoli, Alfredo Oneto, Mar\'ia Parajeles Herrera, Blazhe Gjorgiev, Gabriela Hug, Giovanni Sansavini
https://arxiv.org/abs/2506.08724

Future Deployment and Flexibility of Distributed Energy Resources in the Distribution Grids of Switzerland
The decarbonization goals worldwide drive the energy transition of power distribution grids, which operate under increasingly volatile conditions and closer to their technical limits. In this context, localized operational data with high temporal and spatial resolution is essential for their effective planning and regulation. Nevertheless, information on grid-connected distributed energy resources, such as electric vehicles, photovoltaic systems, and heat pumps, is often fragmented, inconsisten…

Spatial dynamics of flexible nano-swimmers under a rotating magnetic field
Zvi Chapnik, Yizhar Or
https://arxiv.org/abs/2506.07174 https://

Spatial dynamics of flexible nano-swimmers under a rotating magnetic field
Micro-nano-robotic swimmers have promising potential for future biomedical tasks such as targeted drug delivery and minimally-invasive diagnosis. An efficient method for controlled actuation of such nano-swimmers is applying a rotating external magnetic field, resulting in helical corkscrew-like locomotion. In previous joint work, we presented fabrication and actuation of a simple magnetic nano-swimmer composed of two nano-rods connected by a short elastic hinge. Experiments under different act…

Strongly Consistent Community Detection in Popularity Adjusted Block Models
Quan Yuan, Binghui Liu, Danning Li, Lingzhou Xue
https://arxiv.org/abs/2506.07224

Strongly Consistent Community Detection in Popularity Adjusted Block Models
The Popularity Adjusted Block Model (PABM) provides a flexible framework for community detection in network data by allowing heterogeneous node popularity across communities. However, this flexibility increases model complexity and raises key unresolved challenges, particularly in effectively adapting spectral clustering techniques and efficiently achieving strong consistency in label recovery. To address these challenges, we first propose the Thresholded Cosine Spectral Clustering (TCSC) algor…

Wie funktioniert die #Knotenpunktwegweisung in #Brandenburg? 🗺️🚴‍♀️ Mit nummerierten #Knotenpunkten an Kreuzungen kann man in diesem Bundesland eine Route leicht planen und auch …

So funktioniert die Knotenpunktwegweisung in Brandenburg
Erfahre, wie die Knotenpunktwegweisung in Brandenburg funktioniert und wie Du sie für Deine Radtouren nutzen kannst. Einfach orientieren und flexibel planen!

Flexible Operator Fusion for Fast Sparse Transformer with Diverse Masking on GPU
Wenhao Dai, Haodong Deng, Mengfei Rong, Xinyu Yang, Hongyu Liu, Fangxin Liu, Hailong Yang, Weifeng Liu, Qingxiao Sun
https://arxiv.org/abs/2506.06095

Flexible Operator Fusion for Fast Sparse Transformer with Diverse Masking on GPU
Large language models are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerating Transformer through parallelization has gradually become a hot research topic. Mask layers introduce sparsity into Transformer to reduce calculations. However, previous works rarely focus on the performance optimization of sparse Transformer. Moreover, rule-based mechanisms ignore the fusion opportunities of mixed-type operators and fail to adapt to va…

Deep reinforcement learning-based joint real-time energy scheduling for green buildings with heterogeneous battery energy storage devices
Chi Liu, Zhezhuang Xu, Jiawei Zhou, Yazhou Yuan, Kai Ma, Meng Yuan
https://arxiv.org/abs/2506.06824

Deep reinforcement learning-based joint real-time energy scheduling for green buildings with heterogeneous battery energy storage devices
Green buildings (GBs) with renewable energy and building energy management systems (BEMS) enable efficient energy use and support sustainable development. Electric vehicles (EVs), as flexible storage resources, enhance system flexibility when integrated with stationary energy storage systems (ESS) for real-time scheduling. However, differing degradation and operational characteristics of ESS and EVs complicate scheduling strategies. This paper proposes a model-free deep reinforcement learning (…