Tootfinder

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
Denis Zhidkikh, Ville Isom\"ott\"onen, Toni Taipalus
https://arxiv.org/abs/2506.09178

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties in this course is critical for providing targeted support. This study explores the behavioral patterns of CS1 students at varying dropout risks using self-regulated learning (SRL) as the theoretical framework. Using learning analytics, we analyzed trace logs a…

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Dissecting environmental effects with eccentric gravitational wave sources
Lorenz Zwick, Kai Hendriks, David O'Neill, J\'anos Tak\'atsy, Philip Kirkeberg, Christopher Tiede, Jakob Stegmann, Johan Samsing
https://arxiv.org/abs/2506.09140

Dissecting environmental effects with eccentric gravitational wave sources
We model the effect of resonances between time-varying perturbative forces and the epi-cyclical motion of eccentric binaries in the gravitational wave (GW) driven regime. These induce secular drifts in the orbital elements which are reflected in a dephasing of the binary's GW signal, derived here systematically. The resulting dephasing prescriptions showcase a much richer phenomenology with respect to typically adopted power-laws, and are better able to model realistic environmental effects (EE…

TRIDENT -- A Three-Tier Privacy-Preserving Propaganda Detection Model in Mobile Networks using Transformers, Adversarial Learning, and Differential Privacy
Al Nahian Bin Emran, Dhiman Goswami, Md Hasan Ullah Sadi, Sanchari Das
https://arxiv.org/abs/2506.05421

TRIDENT -- A Three-Tier Privacy-Preserving Propaganda Detection Model in Mobile Networks using Transformers, Adversarial Learning, and Differential Privacy
The proliferation of propaganda on mobile platforms raises critical concerns around detection accuracy and user privacy. To address this, we propose TRIDENT - a three-tier propaganda detection model implementing transformers, adversarial learning, and differential privacy which integrates syntactic obfuscation and label perturbation to mitigate privacy leakage while maintaining propaganda detection accuracy. TRIDENT leverages multilingual back-translation to introduce semantic variance, charact…

WAKE: Watermarking Audio with Key Enrichment
Yaoxun Xu, Jianwei Yu, Hangting Chen, Zhiyong Wu, Xixin Wu, Dong Yu, Rongzhi Gu, Yi Luo
https://arxiv.org/abs/2506.05891

WAKE: Watermarking Audio with Key Enrichment
As deep learning advances in audio generation, challenges in audio security and copyright protection highlight the need for robust audio watermarking. Recent neural network-based methods have made progress but still face three main issues: preventing unauthorized access, decoding initial watermarks after multiple embeddings, and embedding varying lengths of watermarks. To address these issues, we propose WAKE, the first key-controllable audio watermark framework. WAKE embeds watermarks using sp…

Using Code Snippets to Teach Programming Languages
Joshua Akingbade, Jianhua Yang, Mir Seyedebrahimi
https://arxiv.org/abs/2506.00404 https://

Using Code Snippets to Teach Programming Languages
Coding is a fundamental skill required in the engineering discipline, and much work exists exploring better ways of teaching coding in the higher education context. In particular, Code Snippets (CSs) are approved to be an effective way of introducing programming language units to students. CSs are portions of source code of varying size and content. They can be used in a myriad of ways, one of which is to teach the code they contain as well as its function. To further explore the use of CSs, a …

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RUBIES: A Spectroscopic Census of Little Red Dots; All V-Shaped Point Sources Have Broad Lines
Raphael E. Hviding, Anna de Graaff, Tim B. Miller, David J. Setton, Jenny E. Greene, Ivo Labb\'e, Gabriel Brammer, Rachel Bezanson, Leindert A. Boogaard, Nikko J. Cleri, Joel Leja, Michael V. Maseda, Ian McConachie, Jorryt Matthee, Rohan P. Naidu, Pascal A. Oesch, Bingjie Wang, Katherine E. Whitaker, Christina Williams

RUBIES: A Spectroscopic Census of Little Red Dots; All V-Shaped Point Sources Have Broad Lines
The physical nature of Little Red Dots (LRDs) - a population of compact, red galaxies revealed by JWST - remains unclear. Photometric samples are constructed from varying selection criteria with limited spectroscopic follow-up available to test intrinsic spectral shapes and prevalence of broad emission lines. We use the RUBIES survey, a large spectroscopic program with wide color-morphology coverage and homogeneous data quality, to systematically analyze the emission-line kinematics, spectral s…

2023 waren wir mit der Schachtour beim 75-jährigen Jubiläum des Schachklub Ersingen. Morgens standen gleich 2 Blitzturniere auf dem Programm und Nachmittag half Chessy dann ein lebendes Schachspiel mit Kindern als Figuren zu veranstalten, zu welchen sich fast das ganze Dorf versammelte um zuzusehen.
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A possible origin of the overlapping light curve of eRO-QPE1
Wen-Long Xu, Hui-Hui Wang, Yi-Gu Chen, Yu-Zhe Li, Wei-Hua Lei
https://arxiv.org/abs/2506.05517

A possible origin of the overlapping light curve of eRO-QPE1
Quasi-Periodic Eruptions (QPEs) are recurrent X-ray eruptions discovered so far in the nuclei of low-mass galaxies. However, despite considerable observational progress, the origin of QPEs remains unclear. A variety of models have been proposed to explain their nature, but a definitive understanding has yet to be reached. Recently, chaotic mixtures of multiple overlapping eruptions with varying amplitudes have been observed in eRO-QPE1 obs1-features not reported in any other known QPE sources. …