Minsk
Russia-Ukraine war: List of key events, day 1,456
How the US left Ukraine exposed to Russia's winter war Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? Russian forces launched multiple attacks on Ukraine's Zaporizhia region, killing one person and injuring seven others over the past day, the region's military administration said on the Telegram messaging platform. The attacks involved 448 drones as well as 163 artillery strikes, causing damage to 136 homes, cars and other structures, the military administration said. Russian forces also continued shelling Ukraine's Donetsk region, forcing 173 people, including 135 children, to evacuate front-line areas over the past day, regional governor Vadym Filashkin said on Telegram.
- Asia > Russia (1.00)
- South America (0.41)
- North America > Central America (0.41)
- (11 more...)
- Information Technology > Communications > Social Media (0.60)
- Information Technology > Artificial Intelligence > Robots > Autonomous Vehicles > Drones (0.52)
Multivariate Time series Anomaly Detection:A Framework of Hidden Markov Models
Li, Jinbo, Pedrycz, Witold, Jamal, Iqbal
In this study, we develop an approach to multivariate time series anomaly detection focused on the transformation of multivariate time series to univariate time series. Several transformation techniques involving Fuzzy C-Means (FCM) clustering and fuzzy integral are studied. In the sequel, a Hidden Markov Model (HMM), one of the commonly encountered statistical methods, is engaged here to detect anomalies in multivariate time series. We construct HMM-based anomaly detectors and in this context compare several transformation methods. A suite of experimental studies along with some comparative analysis is reported.
- North America > Canada > Alberta > Census Division No. 11 > Edmonton Metropolitan Region > Edmonton (0.04)
- North America > Canada > Ontario (0.04)
- North America > United States > New York (0.04)
- (8 more...)
- Banking & Finance (0.69)
- Energy (0.46)
A Mixed-Methods Analysis of Repression and Mobilization in Bangladesh's July Revolution Using Machine Learning and Statistical Modeling
Siddiqui, Md. Saiful Bari, Roy, Anupam Debashis
Abstract--The 2024 July Revolution in Bangladesh represents a landmark event in the study of civil resistance: a successful, student-led civilian uprising that overthrew a long-standing authoritarian regime despite facing brutal state repression. This study investigates the central paradox of its success: how state violence, intended to quell dissent, ultimately fueled the movement's victory. We employ a mixed-methods approach. First, we develop a qualitative narrative of the conflict's timeline to generate specific, testable hypotheses. Then, using a disaggregated, event-level dataset, we employ a multi-method quantitative analysis to dissect the complex relationship between repression and mobilisation. We provide a framework to analyse explosive modern uprisings like the July Revolution. Initial pooled regression models highlight the crucial role of protest momentum (measured by a feedback loop effect) in sustaining the movement. T o isolate causal effects, we specify a Two-Way Fixed Effects panel model, which provides robust evidence for a direct and statistically significant local suppression backfire effect. Our V ector Autoregression (V AR) analysis provides clear visual evidence of an immediate, nationwide mobilisation in response to increased lethal violence. We further demonstrate that this effect was non-linear . A structural break analysis reveals that the backfire dynamic was statistically insignificant in the conflict's early phase but was triggered by the catalytic moral shock of the first wave of lethal violence, and its visuals circulated around July 16th. We conclude that the July Revolution was driven by a contingent, non-linear backfire, triggered by specific catalytic moral shocks and accelerated by the viral reaction to the visual spectacle of state brutality. N August 2024, the fifteen-year rule of Prime Minister Sheikh Hasina of Bangladesh came to a sudden and dramatic end. After weeks of escalating nationwide protests, she resigned from her post and fled the country. These authors contributed equally to this work. Saiful Bari Siddiqui is a Senior Lecturer at the Department of Computer Science and Engineering, BRAC University, Dhaka, Bangladesh (e-mail: saiful.bari@bracu.ac.bd). Anupam Debashis Roy is a PhD candidate at the Department of Sociology, University of Oxford, Oxford, United Kingdom (e-mail: anu-pam.roy@sant.ox.ac.uk). In a matter of weeks, this initial spark grew into a nationwide fire, as hundreds of thousands of ordinary citizens joined the students, bringing the country to a standstill and achieving a political transformation that had seemed unthinkable just a month earlier.
- Europe > United Kingdom > England > Oxfordshire > Oxford (0.54)
- Asia > Bangladesh > Dhaka Division > Dhaka District > Dhaka (0.25)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.14)
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- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
- Government (1.00)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (0.93)
- Law > Civil Rights & Constitutional Law (0.66)
Mechanistic Interpretability with SAEs: Probing Religion, Violence, and Geography in Large Language Models
Simbeck, Katharina, Mahran, Mariam
Despite growing research on bias in large language models (LLMs), most work has focused on gender and race, with little attention to religious identity. This paper explores how religion is internally represented in LLMs and how it intersects with concepts of violence and geography. Using mechanistic interpretability and Sparse Autoencoders (SAEs) via the Neuronpedia API, we analyze latent feature activations across five models. We measure overlap between religion- and violence-related prompts and probe semantic patterns in activation contexts. While all five religions show comparable internal cohesion, Islam is more frequently linked to features associated with violent language. In contrast, geographic associations largely reflect real-world religious demographics, revealing how models embed both factual distributions and cultural stereotypes. These findings highlight the value of structural analysis in auditing not just outputs but also internal representations that shape model behavior.
- North America > United States > New York > New York County > New York City (0.28)
- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- Asia > Middle East > Palestine > Gaza Strip > Gaza Governorate > Gaza (0.14)
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FloorSAM: SAM-Guided Floorplan Reconstruction with Semantic-Geometric Fusion
Ye, Han, Wang, Haofu, Zhang, Yunchi, Xiao, Jiangjian, Jin, Yuqiang, Liu, Jinyuan, Zhang, Wen-An, Sychou, Uladzislau, Tuzikov, Alexander, Sobolevskii, Vladislav, Zakharov, Valerii, Sokolov, Boris, Fu, Minglei
Abstract--Reconstructing building floor plans from point cloud data is a critical technology for indoor navigation, building information modeling (BIM), and highly accurate precise indoor measurement applications. Traditional methods, such as geometric algorithms and Mask R-CNN-based deep learning for mask segmentation, often suffer from sensitivity to noise, limited generalization, and loss of geometric details, severely impacting measurement accuracy. This study proposes an innovative framework, FloorSAM, that integrates room-height point cloud density maps with the guided segmentation capabilities of the Segment Anything Model (SAM) to enhance the precision of floor plan reconstruction from LiDAR point cloud data. By applying grid-based filtering to retain elevation point clouds near the ceiling of each region, combined with adaptive resolution projection and image enhancement techniques, a top-down density map is generated, improving the robustness and accuracy of spatial feature measurement. This framework leverages SAM's zero-shot learning to achieve high-fidelity room segmentation, remarkably enhancing reconstruction and measurement accuracy across diverse building layouts. Subsequently, leveraging SAM's zero-shot guided segmentation capabilities, high-quality room masks are generated based on adaptive prompt points, followed by a multistage filtering process to extract precise semantic masks for individual rooms. Through joint analysis of mask and point cloud modalities, contour extraction and regularization are performed, integrating semantic segmentation with geometric information to produce accurate room floor plans and recover topological relationships between rooms.
- Asia > Russia (0.04)
- Asia > China > Zhejiang Province > Ningbo (0.04)
- Europe > Russia > Northwestern Federal District > Leningrad Oblast > Saint Petersburg (0.04)
- (2 more...)
Belarus and Russia's show of firepower appears to be a message to Europe
Belarus and Russia's show of firepower appears to be a message to Europe In a large field 45 miles (72km) from Belarus' capital Minsk, a battle is raging. There are giant explosions as Sukhoi-34 bombers drop guided bombs. Helicopter gunships join the attack, while surveillance drones sweep overhead to view the damage. Together with other international media we've been brought to the Borisovsky training ground where Belarusian and Russian forces are taking part in joint manoeuvres. Military attachés, too, from a variety of embassies are observing the drill from a viewing platform.
- Asia > Russia (0.97)
- Europe > Belarus > Minsk Region > Minsk (0.29)
- South America (0.15)
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- Government > Military (1.00)
- Government > Regional Government > Europe Government (0.98)
NATO states on alert as Russia and Belarus launch Zapad military drills
How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? Russia and Belarus have begun large-scale military exercises, raising alarm across NATO's eastern flank just days after Warsaw accused Moscow of sending attack drones across Polish airspace, a major escalation that sent shivers through Europe. The Zapad 2025 manoeuvres, which run from Friday until Tuesday, are taking place as Russian forces continue their slow advance in Ukraine and intensify air attacks on Ukrainian cities.
- Asia > Russia (1.00)
- Europe > France (0.33)
- Europe > Russia > Central Federal District > Moscow Oblast > Moscow (0.28)
- (16 more...)
- Government > Military (1.00)
- Government > Regional Government > Europe Government > Russia Government (0.73)
- Government > Regional Government > Asia Government > Russia Government (0.73)
- Information Technology > Artificial Intelligence > Robots > Autonomous Vehicles > Drones (0.36)
- Information Technology > Communications (0.32)
Russia-Ukraine war: List of key events, day 1,296
How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? Anti-aircraft units downed seven Ukrainian drones headed for Moscow early on Friday, according to the Russian capital's mayor Sergei Sobyanin. Russian forces have taken control of the settlement of Sosnivka in Ukraine's Dnipropetrovsk region, Russia's Defence Ministry said on Thursday.
- Asia > Russia (1.00)
- North America > United States (0.50)
- Europe > France (0.31)
- (20 more...)
- Government > Military (1.00)
- Government > Regional Government > Europe Government > Russia Government (0.94)
- Government > Regional Government > Asia Government > Russia Government (0.94)
Recurrence Meets Transformers for Universal Multimodal Retrieval
Caffagni, Davide, Sarto, Sara, Cornia, Marcella, Baraldi, Lorenzo, Cucchiara, Rita
With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have emerged. Existing methods predominantly rely on task-specific fine-tuning of vision-language models and are limited to single-modality queries or documents. In this paper, we propose ReT-2, a unified retrieval model that supports multimodal queries, composed of both images and text, and searches across multimodal document collections where text and images coexist. ReT-2 leverages multi-layer representations and a recurrent Transformer architecture with LSTM-inspired gating mechanisms to dynamically integrate information across layers and modalities, capturing fine-grained visual and textual details. We evaluate ReT-2 on the challenging M2KR and M-BEIR benchmarks across different retrieval configurations. Results demonstrate that ReT-2 consistently achieves state-of-the-art performance across diverse settings, while offering faster inference and reduced memory usage compared to prior approaches. When integrated into retrieval-augmented generation pipelines, ReT-2 also improves downstream performance on Encyclopedic-VQA and InfoSeek datasets. Our source code and trained models are publicly available at: https://github.com/aimagelab/ReT-2
- Oceania > New Zealand (0.04)
- North America > United States > Texas > Collingsworth County (0.04)
- North America > United States > Texas > Camp County (0.04)
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Belarus frees political prisoners in exchange for easing of US sanctions
Dozens of political prisoners have been freed from Belarusian prisons as part of a deal between authoritarian leader Alexander Lukashenko and US President Donald Trump. Fifty-two prisoners have been released, including trade union leaders, journalists and activists, but more than 1,000 political prisoners remain in jail. In exchange, the US has said it will relieve some sanctions on Belarusian airline Belavia, allowing it to buy parts for its airlines. The prisoner release came on the eve of joint military exercises involving Belarus and close ally Russia, and after what neighbouring Poland called an unprecedented Russian drone incursion into its airspace. Poland is closing its borders with Belarus because of the Zapad-2025 drills, which last until Tuesday.
- Government > Regional Government > North America Government > United States Government (1.00)
- Government > Foreign Policy (1.00)