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@blakes7bot@mas.torpidity.net
2025-09-19 06:04:20

#Blakes7 Series C, Episode 06 - City at the Edge of the World
AVON: What the hell is that? [to Dayna, who enters] What happened?
DAYNA: Bayban got away from me.
TARRANT: He'll be making for his ship.
NORL: No! Let him go. He has no men left.

Claude Sonnet 4.0 describes the image as: "In this scene, two characters are engaged in what appears to be a tense conversation aboard a spacecraft. The setting has the distinctive purple-tinted lighting and metallic interior design typical of the series. One character wears a dark leather outfit with metallic studs or details, while the other is dressed in flowing red and dark clothing. They appear to be standing close together in what looks like a corridor or chamber of the ship, suggesting a…
@mpsgoettingen@academiccloud.social
2025-09-15 09:59:20

Following the "Geo-Erlebnis-Tag" during the weekend, preceding the Geo4Göttingen conference, the Geo4Change | Earth, Life, Climate, Resources, Materials | main program will start with plenary sessions for registered conference participants today.
geo4goettingen2025.de/
The full pro…

Front page of a programme booklet, with the conference title and a qr code to the conference web page at the top, and an areal view of part of the city of Göttingen on the bottom two thirds of the front cover. On the sky part of the image, it says in large letters "PROGRAMME".
@arXiv_csCR_bot@mastoxiv.page
2025-09-16 11:50:37

DMLDroid: Deep Multimodal Fusion Framework for Android Malware Detection with Resilience to Code Obfuscation and Adversarial Perturbations
Doan Minh Trung, Tien Duc Anh Hao, Luong Hoang Minh, Nghi Hoang Khoa, Nguyen Tan Cam, Van-Hau Pham, Phan The Duy
arxiv.org/abs/2509.11187

DMLDroid: Deep Multimodal Fusion Framework for Android Malware Detection with Resilience to Code Obfuscation and Adversarial Perturbations
In recent years, learning-based Android malware detection has seen significant advancements, with detectors generally falling into three categories: string-based, image-based, and graph-based approaches. While these methods have shown strong detection performance, they often struggle to sustain robustness in real-world settings, particularly when facing code obfuscation and adversarial examples (AEs). Deep multimodal learning has emerged as a promising solution, leveraging the strengths of mult…