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@carl@heath.social
2025-09-17 21:14:48

På demokratidagen på Åland talade jag om att värna demokratin mot desinformation & digitala hot. Samtalen på fredens öar om tillit, sårbarhet och styrka gav nya perspektiv. Nu finns mina samlade reflektioner i en krönika.
carlheath.se/lardomar-fran-fre

Lärdomar från fredens öar
Planet landade mjukt i ett stilla septemberdis. Mariehamn tog emot med låg horisont, en doft av hav och en påtaglig frånvaro av brådska. Jag var här, på fredens öar…

@toxi@mastodon.thi.ng
2025-07-31 16:24:18

Out & about in the Bernina Range, on our way to the Labyrinth, surrounded by majestic 4000ers (meters)... A dream! 😍
(#ThrowbackThursday, preemptive #FootpathFriday and my personal hiking highlight of 2024)

A glacier side moraine with an almost imperceptible path on its ridge is leading into a sea of ice, rocks and snow in the not so far distance. The massive glacier is just a few dozen meters below from where the picture was taken. It flows & drops down from the peaks in the back (all ~4000m and around 1300m higher up for my position), forming a maze of large seracs on the way. Sunny day with blue sky and some wispy clouds.
View across a large glacier (from the same moraine & position as other photo) towards the opposite side of the valley with its 4000m peaks, hidden below a thick layer of snow and ice, some side glaciers and bare major rock faces dusted in snow. Some dried brown grass in the bottom-right corner.
@arXiv_csNI_bot@mastoxiv.page
2025-07-01 09:02:23

Service Placement in Small Cell Networks Using Distributed Best Arm Identification in Linear Bandits
Mariam Yahya, Aydin Sezgin, Setareh Maghsudi
arxiv.org/abs/2506.22480 …

Service Placement in Small Cell Networks Using Distributed Best Arm Identification in Linear Bandits
As users in small cell networks increasingly rely on computation-intensive services, cloud-based access often results in high latency. Multi-access edge computing (MEC) mitigates this by bringing computational resources closer to end users, with small base stations (SBSs) serving as edge servers to enable low-latency service delivery. However, limited edge capacity makes it challenging to decide which services to deploy locally versus in the cloud, especially under unknown service demand and dy…

@arXiv_physicsmedph_bot@mastoxiv.page
2025-07-23 07:56:02

Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging
Mohammad R. Salmanpour, Somayeh Sadat Mehrnia, Sajad Jabarzadeh Ghandilu, Zhino Safahi, Sonya Falahati, Shahram Taeb, Ghazal Mousavi, Mehdi Maghsoudi, Ahmad Shariftabrizi, Ilker Hacihaliloglu, Arman Rahmim

Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging
Machine learning (ML), including deep learning (DL) and radiomics-based methods, is increasingly used for cancer outcome prediction with PET and SPECT imaging. However, the comparative performance of handcrafted radiomics features (HRF), deep radiomics features (DRF), DL models, and hybrid fusion approaches remains inconsistent across clinical applications. This systematic review analyzed 226 studies published from 2020 to 2025 that applied ML to PET or SPECT imaging for outcome prediction. Eac…