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@Mediagazer@mstdn.social
2025-06-06 17:46:07

UK satellite TV channel Islam Channel acquires politics magazine Tribune, plans to increase its print frequency, and launch new formats like podcasts and video (Rob Waugh/Press Gazette)
pressgazette.co.uk/publishers/

UK political mag Tribune taken over by Islam Channel owner
Tribune magazine has been bought by the Islam Channel, former editor said "one of weirdest things to have happened history of British media

@dawid@social.craftknight.com
2025-07-06 12:41:33
@…

Obecnie Islam to niewielki procent 3-5, do 2050 przy dużej imigracji może dojdzie do 15% https://en.wikipedia.org/wiki/Islam_in_Europe.

Osób, które porzucają Islam jest więcej niż konwersji na Islam w UE, co w momencie zatrzymania imigracji spowoduje też spade…
@arXiv_grqc_bot@mastoxiv.page
2025-07-14 08:46:21

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation
Digvijay Wadekar, Arush Pimpalkar, Mark Ho-Yeuk Cheung, Benjamin Wandelt, Emanuele Berti, Ajit Kumar Mehta, Tejaswi Venumadhav, Javier Roulet, Tousif Islam, Barak Zackay, Jonathan Mushkin, Matias Zaldarriaga
…

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation
We introduce a machine learning (ML) framework called $\texttt{TIER}$ for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a small region of strain data in the vicinity of a candidate signal to construct the detection statistic. However, extended strain data ($\sim 10$ s) in the candidate's vicinity can also carry valuable complementary information. We show that this information can be efficiently captured by ML classifier models trained on …

@arXiv_csCV_bot@mastoxiv.page
2025-07-10 08:45:41

EA: An Event Autoencoder for High-Speed Vision Sensing
Riadul Islam, Joey Mul\'e, Dhandeep Challagundla, Shahmir Rizvi, Sean Carson
arxiv.org/abs/2507.06459

EA: An Event Autoencoder for High-Speed Vision Sensing
High-speed vision sensing is essential for real-time perception in applications such as robotics, autonomous vehicles, and industrial automation. Traditional frame-based vision systems suffer from motion blur, high latency, and redundant data processing, limiting their performance in dynamic environments. Event cameras, which capture asynchronous brightness changes at the pixel level, offer a promising alternative but pose challenges in object detection due to sparse and noisy event streams. To…

@arXiv_condmatsuprcon_bot@mastoxiv.page
2025-06-12 08:59:01

Emergent anisotropic three-phase order in critically doped superconducting diamond films
Jyotirmay Dwivedi, Jake Morris, Saurav Islam, Kalana D. Halanayake, Gabriel A. Vazquez-Lizardi, David Snyder, Anthony Richardella, Luke Lyle, Danielle Reifsnyder Hickey, Nazar Delegan, F. Joseph Heremans, David D. Awschalom, Nitin Samarth

Emergent anisotropic three-phase order in critically doped superconducting diamond films
Two decades since its discovery, superconducting heavily boron-doped diamond (HBDD) still presents unresolved fundamental questions whose resolution is relevant to the development of this material for quantum technologies. We use electrical magnetotransport measurements of critically-doped homoepitaxial single crystal HBDD films to reveal signatures of intrinsic (electronic) granular superconductivity. By studying the dependence of electrical resistivity on temperature and magnetic field vector…

@arXiv_csNE_bot@mastoxiv.page
2025-06-06 07:20:09

A Comprehensive Survey on Bio-Inspired Algorithms: Taxonomy, Applications, and Future Directions
Shriyank Somvanshi, Md Monzurul Islam, Syed Aaqib Javed, Gaurab Chhetri, Kazi Sifatul Islam, Tausif Islam Chowdhury, Sazzad Bin Bashar Polock, Anandi Dutta, Subasish Das
arxiv.org/abs/2506.04238

A Comprehensive Survey on Bio-Inspired Algorithms: Taxonomy, Applications, and Future Directions
Bio-inspired algorithms (BIAs) utilize natural processes such as evolution, swarm behavior, foraging, and plant growth to solve complex, nonlinear, high-dimensional optimization problems. This survey categorizes BIAs into eight groups: evolutionary, swarm intelligence, physics-inspired, ecosystem and plant-based, predator-prey, neural-inspired, human-inspired, and hybrid approaches, and reviews their core principles, strengths, and limitations. We illustrate the usage of these algorithms in mac…

@arXiv_csIR_bot@mastoxiv.page
2025-06-10 08:09:42

Correcting for Position Bias in Learning to Rank: A Control Function Approach
Md Aminul Islam, Kathryn Vasilaky, Elena Zheleva
arxiv.org/abs/2506.06989

Correcting for Position Bias in Learning to Rank: A Control Function Approach
Implicit feedback data, such as user clicks, is commonly used in learning-to-rank (LTR) systems because it is easy to collect and it often reflects user preferences. However, this data is prone to various biases, and training an LTR system directly on biased data can result in suboptimal ranking performance. One of the most prominent and well-studied biases in implicit feedback data is position bias, which occurs because users are more likely to interact with higher-ranked documents regardless …

@arXiv_csSE_bot@mastoxiv.page
2025-07-04 08:16:11

Can Internal Software Metrics Predict App Popularity at Launch? Yeas! and Nays!
Md Nahidul Islam Opu, Fatima Islam Mouri, Rick Kazman, Yuanfang Cai, Shaiful Chowdhury
arxiv.org/abs/2507.02110

Can Internal Software Metrics Predict App Popularity at Launch? Yeas! and Nays!
Predicting mobile app popularity before release can provide developers with a strategic advantage in a competitive marketplace, yet it remains a challenging problem. This study explores whether internal software metrics, measurable from source code before deployment, can predict an app's popularity, defined by user ratings (calculated from user reviews) and DownloadsPerYear (yearly downloads). Using a dataset of 446 open-source Android apps from F-Droid, we extract a wide array of features, inc…

@arXiv_grqc_bot@mastoxiv.page
2025-06-12 08:49:41

York's Cavity Formalism and Quantum Modified Thermodynamics of (2 1)D Black Holes
Prince A Ganai, Nadeem Ul Islam, Nazir A Ganaie
arxiv.org/abs/2506.09086

York's Cavity Formalism and Quantum Modified Thermodynamics of (2+1)D Black Holes
We investigate the thermodynamic behavior of $(2+1)$ dimensional BTZ black holes using York's cavity formalism, in which the black hole is enclosed within a finite-radius boundary held at a fixed temperature. This canonical ensemble construction enables the precise derivation of thermodynamic quantities such as temperature, energy, entropy, pressure, and heat capacity via the integral Euclidean path approach. Extending this analysis, we incorporate quantum corrections through Barrow entropy, a …

@arXiv_csSD_bot@mastoxiv.page
2025-06-09 07:58:32

WhisQ: Cross-Modal Representation Learning for Text-to-Music MOS Prediction
Jakaria Islam Emon, Kazi Tamanna Alam, Md. Abu Salek
arxiv.org/abs/2506.05899

WhisQ: Cross-Modal Representation Learning for Text-to-Music MOS Prediction
Mean Opinion Score (MOS) prediction for text to music systems requires evaluating both overall musical quality and text prompt alignment. This paper introduces WhisQ, a multimodal architecture that addresses this dual-assessment challenge through sequence level co-attention and optimal transport regularization. WhisQ employs the Whisper Base pretrained model for temporal audio encoding and Qwen 3, a 0.6B Small Language Model (SLM), for text encoding, with both maintaining sequence structure for…

@arXiv_csDL_bot@mastoxiv.page
2025-05-27 07:19:28

A Domain Ontology for Modeling the Book of Purification in Islam
Hessa Alawwad
arxiv.org/abs/2505.18222 arxiv.org/pdf…

A Domain Ontology for Modeling the Book of Purification in Islam
This paper aims to address a gap in major Islamic topics by developing an ontology for the Book of Purification in Islam. Many authoritative Islamic texts begin with the Book of Purification, as it is essential for performing prayer (the second pillar of Islam after Shahadah, the profession of faith) and other religious duties such as Umrah and Hajj. The ontology development strategy followed six key steps: (1) domain identification, (2) knowledge acquisition, (3) conceptualization, (4) class…

@arXiv_physicsoptics_bot@mastoxiv.page
2025-06-10 11:03:52

Tunable Coloration in Core-Shell Plasmonic Nanopixels Based on Organic Conductive Polymers: A First-Principles and FDTD Study
Md. Shariful Islam, Ahmed Zubair
arxiv.org/abs/2506.07544

Tunable Coloration in Core-Shell Plasmonic Nanopixels Based on Organic Conductive Polymers: A First-Principles and FDTD Study
From raindrops to planets, the scattering of electromagnetic fields introduces exciting phenomena that can be utilized for display devices. Here, we designed an electrochromic nanoparticle on mirror (eNPoM) structure with core-shell geometries for low-power nanoscale pixels with rapid coloration abilities based on four electrochromic organic conducting polymers utilizing the first-principles calculations based on density functional theory (DFT) and the finite-difference time-domain (FDTD) simul…

@arXiv_csCV_bot@mastoxiv.page
2025-07-10 10:15:41

GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning
S M Taslim Uddin Raju, Md. Milon Islam, Md Rezwanul Haque, Hamdi Altaheri, Fakhri Karray
arxiv.org/abs/2507.07006

GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning
Microscopic assessment of histopathology images is vital for accurate cancer diagnosis and treatment. Whole Slide Image (WSI) classification and captioning have become crucial tasks in computer-aided pathology. However, microscopic WSI face challenges such as redundant patches and unknown patch positions due to subjective pathologist captures. Moreover, generating automatic pathology captions remains a significant challenge. To address these issues, we introduce a novel GNN-ViTCap framework for…

@arXiv_csLG_bot@mastoxiv.page
2025-06-25 07:37:19

From Tiny Machine Learning to Tiny Deep Learning: A Survey
Shriyank Somvanshi, Md Monzurul Islam, Gaurab Chhetri, Rohit Chakraborty, Mahmuda Sultana Mimi, Swagat Ahmed Shuvo, Kazi Sifatul Islam, Syed Aaqib Javed, Sharif Ahmed Rafat, Anandi Dutta, Subasish Das
arxiv.org/abs/2506.18927…

From Tiny Machine Learning to Tiny Deep Learning: A Survey
The rapid growth of edge devices has driven the demand for deploying artificial intelligence (AI) at the edge, giving rise to Tiny Machine Learning (TinyML) and its evolving counterpart, Tiny Deep Learning (TinyDL). While TinyML initially focused on enabling simple inference tasks on microcontrollers, the emergence of TinyDL marks a paradigm shift toward deploying deep learning models on severely resource-constrained hardware. This survey presents a comprehensive overview of the transition from…

@arXiv_physicsappph_bot@mastoxiv.page
2025-07-10 09:04:51

High-Performance Self-Powered Photoelectrochemical Detection Using Scalable InGaN/GaN Nanowire Arrays
Kishan Lal Kumawat, Md. Afjalur Rahman, Nirmal Anand, Dipon Kumar Ghosh, Christy Giji Jenson, Md. Moinul Islam, Samuel Olakunle Adigbo, Sheik Munim Hussain, Md Zunaid Baten, Sharif Md. Sadaf
arxiv.org/abs/2507.06501

High-Performance Self-Powered Photoelectrochemical Detection Using Scalable InGaN/GaN Nanowire Arrays
Photoelectrochemical photodetectors (PEC-PDs) are promising owing to their simple, low-cost fabrication, self-powered operation, high photoresponse, and environmental sensitivity. In this work, we report for the first time the self-powered PEC photodetection characteristics of nanowire (NW) based green-emitting InGaN/GaN multiple quantum well (MQW) PEC-PDs, fabricated via a scalable top-down approach.The device exhibits strong UV sensitivity with a peak at 365 nm and an extended response into t…

@arXiv_csCL_bot@mastoxiv.page
2025-07-03 10:16:50

Adaptability of ASR Models on Low-Resource Language: A Comparative Study of Whisper and Wav2Vec-BERT on Bangla
Md Sazzadul Islam Ridoy, Sumi Akter, Md. Aminur Rahman
arxiv.org/abs/2507.01931

Adaptability of ASR Models on Low-Resource Language: A Comparative Study of Whisper and Wav2Vec-BERT on Bangla
In recent years, neural models trained on large multilingual text and speech datasets have shown great potential for supporting low-resource languages. This study investigates the performances of two state-of-the-art Automatic Speech Recognition (ASR) models, OpenAI's Whisper (Small & Large-V2) and Facebook's Wav2Vec-BERT on Bangla, a low-resource language. We have conducted experiments using two publicly available datasets: Mozilla Common Voice-17 and OpenSLR to evaluate model performances. Th…

@arXiv_csCV_bot@mastoxiv.page
2025-07-10 08:54:01

Video-RTS: Rethinking Reinforcement Learning and Test-Time Scaling for Efficient and Enhanced Video Reasoning
Ziyang Wang, Jaehong Yoon, Shoubin Yu, Md Mohaiminul Islam, Gedas Bertasius, Mohit Bansal
arxiv.org/abs/2507.06485

Video-RTS: Rethinking Reinforcement Learning and Test-Time Scaling for Efficient and Enhanced Video Reasoning
Despite advances in reinforcement learning (RL)-based video reasoning with large language models (LLMs), data collection and finetuning remain significant challenges. These methods often rely on large-scale supervised fine-tuning (SFT) with extensive video data and long Chain-of-Thought (CoT) annotations, making them costly and hard to scale. To address this, we present Video-RTS, a new approach to improve video reasoning capability with drastically improved data efficiency by combining data-ef…

@arXiv_eessIV_bot@mastoxiv.page
2025-06-04 07:35:40

Dual encoding feature filtering generalized attention UNET for retinal vessel segmentation
Md Tauhidul Islam, Wu Da-Wen, Tang Qing-Qing, Zhao Kai-Yang, Yin Teng, Li Yan-Fei, Shang Wen-Yi, Liu Jing-Yu, Zhang Hai-Xian
arxiv.org/abs/2506.02312

Dual encoding feature filtering generalized attention UNET for retinal vessel segmentation
Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases. Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field, yet issues like limited training data, imbalance data distribution, and inadequate feature extraction persist, hindering both the segmentation performance and optimal model generalization. Addressing these critical issues, the DEFFA-Unet is proposed featuring an additional encoder to process domain-invar…

@Life_is@no-pony.farm
2025-06-17 21:05:17

Aische war die erste Imanin einer neu gegründeten Religion namens Islam. Wesentlich bekannter ist allerdings ihr Ehepartner Mohammed, der häufig als Prophet bezeichnet wird.

@life_is@no-pony.farm
2025-06-17 21:05:17

Aische war die erste Imanin einer neu gegründeten Religion namens Islam. Wesentlich bekannter ist allerdings ihr Ehepartner Mohammed, der häufig als Prophet bezeichnet wird.

@arXiv_csSE_bot@mastoxiv.page
2025-07-08 11:01:41

Exploring React Library Related Questions on Stack Overflow: Answered vs. Unanswered
Vanesya Aura Ardity, Yusuf Sulistyo Nugroho, Syful Islam
arxiv.org/abs/2507.04390

Exploring React Library Related Questions on Stack Overflow: Answered vs. Unanswered
React is a popular JavaScript framework in modern web application development. Due to its high performance and efficiency, many developers use this framework. Although React library offers many advantages, it is not without its challenges. When using React library, developers often face problems where they often seek solutions through question-and-answer forums, such as Stack Overflow (SO). However, despite its high popularity, many React-related questions on SO remain unanswered. Thus, this st…

@dawid@social.craftknight.com
2025-07-06 12:06:56
@…

W miejsce chrześcijaństwa we Francji czy Niemczech nie wchodzi Islam - wzrost procenta wierzących muzułmanów jest czysto demograficzny i związany z imigracją. To co następuje to dynamiczna laicyzacja - szybsza wśród chrześcijan, ale i rosnąca wśród 2 pokolenia imigrantów innych religii. To też nie zaburza kultury - okazuje się, że brak…
@arXiv_eessSY_bot@mastoxiv.page
2025-06-03 07:31:55

Sensor Fusion Methods for Gaussian Mixture Models
Ishan Paranjape, Islam Hussein, Jeremy Murray-Krezan, Sean Phillips, Suman Chakravorty
arxiv.org/abs/2506.00383

Sensor Fusion Methods for Gaussian Mixture Models
Consensus is a popular technique for distributed state estimation. This formulation allows networks of connected agents or sensors to exchange information about the distribution of a set of targets with their immediate neighbors without the need of a centralized node or layer. We present decentralized consensus-based fusion techniques for a system whose target prior estimates are a weighted mixture of Gaussian probability density functions (PDFs) for the following cases: 1) in which all agents …

@arXiv_condmatsuprcon_bot@mastoxiv.page
2025-07-10 08:59:31

Discovery of High-Temperature Charge Order and Time-Reversal Symmetry-Breaking in the Kagome Superconductor YRu3Si2
P. Kr\`al, J. N. Graham, V. Sazgari, I. Plokhikh, A. Lukovkina, O. Gerguri, I. Bialo, A. Doll, L. Martinelli, J. Oppliger, S. S. Islam, K. Wang, M. Salamin, H. Luetkens, R. Khasanov, M. v. Zimmermann, J. -X. Yin, Ziqiang Wang, J. Chang, B. Monserrat, D. Gawryluk, F. O. von Rohr, S. -W. Kim, Z. Guguchia

Discovery of High-Temperature Charge Order and Time-Reversal Symmetry-Breaking in the Kagome Superconductor YRu3Si2
The identification of high-temperature unconventional charge order and superconductivity in kagome quantum materials is pivotal for deepening our understanding of geometrically frustrated and correlated electron systems, and for harnessing their exotic properties in future quantum technologies. Here, we report the discovery of a remarkably rich phase diagram in the kagome superconductor YRu$_{3}$Si$_{2}$, uncovered through a unique combination of muon spin rotation ($μ$SR), magnetotransport, X…

@arXiv_eessSP_bot@mastoxiv.page
2025-07-01 11:43:33

Optimizing Solar Energy Production in the USA: Time-Series Analysis Using AI for Smart Energy Management
Istiaq Ahmed, Md Asif Ul Hoq Khan, MD Zahedul Islam, Md Sakibul Hasan, Tanaya Jakir, Arat Hossain, Joynal Abed, Muhammad Hasanuzzaman, Sadia Sharmeen Shatyi, Kazi Nehal Hasnain
arxiv.org/abs/2506.23368

Optimizing Solar Energy Production in the USA: Time-Series Analysis Using AI for Smart Energy Management
As the US rapidly moves towards cleaner energy sources, solar energy is fast becoming the pillar of its renewable energy mix. Even while solar energy is increasingly being used, its variability is a key hindrance to grid stability, storage efficiency, and system stability overall. Solar energy has emerged as one of the fastest-growing renewable energy sources in the United States, adding noticeably to the country's energy mix. Retrospectively, the necessity of inserting the sun's energy into th…

@arXiv_csPF_bot@mastoxiv.page
2025-06-05 07:20:30

WANDER: An Explainable Decision-Support Framework for HPC
Ankur Lahiry, Banooqa Banday, Tanzima Z. Islam
arxiv.org/abs/2506.04049

WANDER: An Explainable Decision-Support Framework for HPC
High-performance computing (HPC) systems expose many interdependent configuration knobs that impact runtime, resource usage, power, and variability. Existing predictive tools model these outcomes, but do not support structured exploration, explanation, or guided reconfiguration. We present WANDER, a decision-support framework that synthesizes alternate configurations using counterfactual analysis aligned with user goals and constraints. We introduce a composite trade-off score that ranks sugges…

@arXiv_csCR_bot@mastoxiv.page
2025-06-26 07:32:30

Secure Energy Transactions Using Blockchain Leveraging AI for Fraud Detection and Energy Market Stability
Md Asif Ul Hoq Khan, MD Zahedul Islam, Istiaq Ahmed, Md Masud Karim Rabbi, Farhana Rahman Anonna, MD Abdul Fahim Zeeshan, Mehedi Hasan Ridoy, Bivash Ranjan Chowdhury, Md Nazmul Shakir Rabbi, GM Alamin Sadnan
arxiv.or…

Secure Energy Transactions Using Blockchain Leveraging AI for Fraud Detection and Energy Market Stability
Peer-to-peer trading and the move to decentralized grids have reshaped the energy markets in the United States. Notwithstanding, such developments lead to new challenges, mainly regarding the safety and authenticity of energy trade. This study aimed to develop and build a secure, intelligent, and efficient energy transaction system for the decentralized US energy market. This research interlinks the technological prowess of blockchain and artificial intelligence (AI) in a novel way to solve lon…

@arXiv_csDC_bot@mastoxiv.page
2025-06-27 09:28:09

Enabling Bitcoin Smart Contracts on the Internet Computer
Ryan Croote, Islam El-Ashi, Thomas Locher, Yvonne-Anne Pignolet
arxiv.org/abs/2506.21327

Enabling Bitcoin Smart Contracts on the Internet Computer
There is growing interest in providing programmatic access to the value locked in Bitcoin, which famously offers limited programmability itself. Various approaches have been put forth in recent years, with the vast majority of proposed mechanisms either building new functionality on top of Bitcoin or leveraging a bridging mechanism to enable smart contracts that make use of ``wrapped'' bitcoins on entirely different platforms. In this work, an architecture is presented that follows a differen…

@Jackobli@mastodon.social
2025-05-20 11:13:19

…Es bestehe der Verdacht, dass Schach eine Quelle für Glücksspiel sei und somit nicht mit dem Islam vereinbar…
Vermutlich sind auch Hähne verboten, denn die könnten ja auch für Hahnenkämpfe um Geld verwendet werden.
Echt, diese Bande von Steinzeitmännern braucht's nicht. 🤬

Afghanistan unter der Scharia: Taliban verbieten Schach
Ein afghanischer Schach-Champion setzt sich nach Deutschland ab. Er könne ohne Schach nicht leben, sagt er.

@arXiv_csCV_bot@mastoxiv.page
2025-07-08 23:22:20

Replaced article(s) found for cs.CV. arxiv.org/list/cs.CV/new
[10/10]:
- Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reas...
Laskar, Islam, Mahbub, Masry, Rahman, Bhuiyan, Nayeem, Joty, Hoque, Huang

@goebelmasse@det.social
2025-06-19 12:13:12

Ist alt, aber passt immer noch.

Werbeaufsteller am Straßenrand vor einem Kiosk. Bildzeitungswerbung mit damals tagesaktueller Schlagzeile »Was genau am Islam den Leuten Angst macht«. Darunter groß das Logo der Bildzeitung.
@arXiv_qbiobm_bot@mastoxiv.page
2025-07-01 09:08:03

Rotational Dynamics of ATP Synthase: Mechanical Constraints and Energy Dissipative Channels
Islam K. Matar, Peyman Fahimi, Cherif F. Matta
arxiv.org/abs/2506.23439

Rotational Dynamics of ATP Synthase: Mechanical Constraints and Energy Dissipative Channels
The proton motive force (PMF) across the inner mitochondrial membrane delivers approximately 0.2 eV of energy per proton, powering the FoF1-ATP synthase molecular motor. Here, we provide a detailed accounting of how this energy is utilized: Approximately 75-83% is transduced into the chemical free energy of ATP synthesis, while the remaining 17-25% is dissipated through internal friction, viscous drag, proton leakage, electroviscous effects, elastic deformations, and information-theoretic costs…

@arXiv_statML_bot@mastoxiv.page
2025-06-24 18:13:10

Replaced article(s) found for stat.ML. arxiv.org/list/stat.ML/new
[2/2]:
- Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset...
Azmine Toushik Wasi, MD Shafikul Islam, Adipto Raihan Akib, Mahathir Mohammad Bappy

@arXiv_statME_bot@mastoxiv.page
2025-06-25 08:51:50

A Bayesian approach for unadjudicated events in cardiovascular disease cohort studies
Mirajul Islam, Michael J. Daniels, Donald Lloyd-Jones, Juned Siddique
arxiv.org/abs/2506.19066

A Bayesian approach for unadjudicated events in cardiovascular disease cohort studies
An important issue in joint modelling for outcomes and longitudinal risk factors in cohort studies is to have an accurate assessment of events. Events determined based on ICD-9 codes can be very inaccurate, in particular for cardiovascular disease (CVD) where ICD-9 codes may overestimate the frequency of CVD. Motivated by the lack of adjudicated events in the Established Populations for Epidemiologic Studies of the Elderly (EPESE) cohort, we develop methods that use a related cohort Atheroscler…

@arXiv_eessIV_bot@mastoxiv.page
2025-07-01 08:37:43

Multi-Domain FeFET-Based Pixel for In-Sensor Multiply-and-Accumulate Operations
Md Rahatul Islam Udoy, Wantong Li, Kai Ni, Ahmedullah Aziz
arxiv.org/abs/2506.22596

Multi-Domain FeFET-Based Pixel for In-Sensor Multiply-and-Accumulate Operations
This paper presents an FeFET-based active pixel sensor that performs in-sensor multiply-and-accumulate (MAC) operations by leveraging the multi-domain polarization states of ferroelectric layers. The proposed design integrates a programmable FeFET into a 3-transistor pixel circuit, where the FeFET's non-volatile conductance encodes the weight, and the photodiode voltage drop encodes the input. Their interaction generates an output current proportional to the product, enabling in-pixel analog mu…

@arXiv_csSD_bot@mastoxiv.page
2025-07-02 08:26:59

A High-Fidelity Speech Super Resolution Network using a Complex Global Attention Module with Spectro-Temporal Loss
Tarikul Islam Tamiti, Biraj Joshi, Rida Hasan, Rashedul Hasan, Taieba Athay, Nursad Mamun, Anomadarshi Barua
arxiv.org/abs/2507.00229

A High-Fidelity Speech Super Resolution Network using a Complex Global Attention Module with Spectro-Temporal Loss
Speech super-resolution (SSR) enhances low-resolution speech by increasing the sampling rate. While most SSR methods focus on magnitude reconstruction, recent research highlights the importance of phase reconstruction for improved perceptual quality. Therefore, we introduce CTFT-Net, a Complex Time-Frequency Transformation Network that reconstructs both magnitude and phase in complex domains for improved SSR tasks. It incorporates a complex global attention block to model inter-phoneme and inte…

@arXiv_csDC_bot@mastoxiv.page
2025-06-27 08:47:09

Scalable GPU Performance Variability Analysis framework
Ankur Lahiry, Ayush Pokharel, Seth Ockerman, Amal Gueroudji, Line Pouchard, Tanzima Z. Islam
arxiv.org/abs/2506.20674

Scalable GPU Performance Variability Analysis framework
Analyzing large-scale performance logs from GPU profilers often requires terabytes of memory and hours of runtime, even for basic summaries. These constraints prevent timely insight and hinder the integration of performance analytics into automated workflows. Existing analysis tools typically process data sequentially, making them ill-suited for HPC workflows with growing trace complexity and volume. We introduce a distributed data analysis framework that scales with dataset size and compute av…

@arXiv_csSE_bot@mastoxiv.page
2025-06-16 10:18:49

Understanding the Issue Types in Open Source Blockchain-based Software Projects with the Transformer-based BERTopic
Md Nahidul Islam Opu, Md Shahidul Islam, Sara Rouhani, Shaiful Chowdhury
arxiv.org/abs/2506.11451

Understanding the Issue Types in Open Source Blockchain-based Software Projects with the Transformer-based BERTopic
Blockchain-based software systems are increasingly deployed across diverse domains, yet a systematic understanding of their development challenges remains limited. This paper presents a large-scale empirical study of 497,742 issues mined from 1,209 open-source blockchain projects hosted on GitHub. Employing BERTopic, a transformer-based topic modeling technique, we identify 49 distinct issue topics and organize them hierarchically into 11 major subcategories. Our analysis reveals that both gene…

@arXiv_nlincd_bot@mastoxiv.page
2025-07-03 13:02:48

Replaced article(s) found for nlin.CD. arxiv.org/list/nlin.CD/new
[1/1]:
- Protected chaos in a topological lattice
Sahin, Akg\"un, Bin Siu, Rafi-Ul-Islam, Kong, Jalil, Lee

@arXiv_grqc_bot@mastoxiv.page
2025-07-03 08:16:40

Searching for intermediate mass ratio binary black hole mergers in the third observing run of LIGO-Virgo-KAGRA
Mark Ho-Yeuk Cheung, Digvijay Wadekar, Ajit Kumar Mehta, Tousif Islam, Javier Roulet, Emanuele Berti, Tejaswi Venumadhav, Barak Zackay, Matias Zaldarriaga
arxiv.org/abs/2507.01083

Searching for intermediate mass ratio binary black hole mergers in the third observing run of LIGO-Virgo-KAGRA
Intermediate mass ratio inspirals (IMRIs) of binary black holes with mass ratios $10^{-4}\lesssim q \lesssim 0.1$ are astrophysically interesting sources of gravitational waves. Mergers of intermediate-mass black holes (IMBHs) with stellar-mass black holes would be IMRIs, so their detection can help us probe the formation mechanisms of IMBHs. They can also help us perform precise tests of general relativity due to the presence of strong higher-order mode emission. We perform a search for aligne…

@arXiv_eessIV_bot@mastoxiv.page
2025-07-01 10:06:53

SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting
Yiming Huang, Long Bai, Beilei Cui, Kun Yuan, Guankun Wang, Mobarakol Islam, Nicolas Padoy, Nassir Navab, Hongliang Ren
arxiv.org/abs/2506.23309

SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting
In contemporary surgical research and practice, accurately comprehending 3D surgical scenes with text-promptable capabilities is particularly crucial for surgical planning and real-time intra-operative guidance, where precisely identifying and interacting with surgical tools and anatomical structures is paramount. However, existing works focus on surgical vision-language model (VLM), 3D reconstruction, and segmentation separately, lacking support for real-time text-promptable 3D queries. In thi…

@arXiv_statME_bot@mastoxiv.page
2025-06-24 10:56:20

Personalized feature threshold estimation in joint modelling of longitudinal and time-to-event data
Mirajul Islam, Michael J. Daniels, Juned Siddique
arxiv.org/abs/2506.17835

Personalized feature threshold estimation in joint modelling of longitudinal and time-to-event data
Cardiovascular disease (CVD) cohort studies collect longitudinal data on numerous CVD risk factors including body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, and total cholesterol. The commonly used threshold values for identifying subjects at high risk are 30 kg/$m^2$ for BMI, 120 mmHg for SBP, 80 mmHg for DBP, 126 mg/dL for glucose, and 230 mg/dL for total cholesterol. When studying the association between features of longitudinal risk factors and…

@arXiv_csSD_bot@mastoxiv.page
2025-06-30 08:51:30

Reconstructing Intelligible Speech from the Pressure Sensor Data in HVACs
Tarikul Islam Tamiti, Biraj Joshi, Rida Hasan, Anomadarshi Barua
arxiv.org/abs/2506.22311

Reconstructing Intelligible Speech from the Pressure Sensor Data in HVACs
Pressure sensors are an integrated component of modern Heating, Ventilation, and Air Conditioning (HVAC) systems. As these pressure sensors operate within the 0-10 Pa range, support high sampling frequencies of 0.5-2 kHz, and are often placed close to human proximity, they can be used to eavesdrop on confidential conversation, since human speech has a similar audible range of 0-10 Pa and a bandwidth of 4 kHz for intelligible quality. This paper presents WaLi, which reconstructs intelligible spe…

@arXiv_eessSP_bot@mastoxiv.page
2025-06-19 08:44:17

Urban RIS-Assisted HAP Networks: Performance Analysis Using Stochastic Geometry
Islam M. Tanash, Ayush Kumar Dwivedi, Taneli Riihonen
arxiv.org/abs/2506.15338

Urban RIS-Assisted HAP Networks: Performance Analysis Using Stochastic Geometry
This paper studies a high-altitude platform (HAP) network supported by reconfigurable intelligent surfaces (RISs). The practical irregular placement of HAPs and RISs is modeled using homogeneous Poisson point processes, while buildings that cause blockages in urban areas are modeled as a Boolean scheme of rectangles. We introduce a novel approach to characterize the statistical channel based on generalized Beta prime distribution. Analytical expressions for coverage probability and ergodic capa…

@arXiv_physicsoptics_bot@mastoxiv.page
2025-06-24 10:26:10

Exceptional point in a PT symmetric non-Hermitian terahertz plasmonic metasurface
Anshul Bhardwaj, Maidul Islam, Chandan Kumar, Anuraj Panwar, Gagan Kumar
arxiv.org/abs/2506.17906

Exceptional point in a PT symmetric non-Hermitian terahertz plasmonic metasurface
In this paper, we experimentally demonstrate a non-Hermitian open PT-symmetric terahertz metasurface comprising complementary plasmonic structures capable of exhibiting an exceptional point (EP). The metasurface consists of two resonators of different sizes, representing effective gain and loss elements, placed orthogonally in close proximity to realize a non-Hermitian configuration leading to a PT symmetry state. A diagonal displacement of one resonator within this strongly coupled near-field …

@arXiv_csSD_bot@mastoxiv.page
2025-06-30 08:59:20

A Practical Approach to Power Saving in Hearables Using Sub-Nyquist Sampling with Bandwidth Extension
Tarikul Islam Tamiti, Anomadarshi Barua
arxiv.org/abs/2506.22321

A Practical Approach to Power Saving in Hearables Using Sub-Nyquist Sampling with Bandwidth Extension
Hearables are wearable computers that are worn on the ear. Bone conduction microphones (BCMs) are used with air conduction microphones (ACMs) in hearables as a supporting modality for multimodal speech enhancement (SE) in noisy conditions. However, existing works don't consider the following practical aspects for low-power implementations on hearables: (i) They do not explore how lowering the sampling frequencies and bit resolutions in analog-to-digital converters (ADCs) of hearables jointly im…

@arXiv_eessIV_bot@mastoxiv.page
2025-06-23 08:59:30

D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI Synthesis
Sanuwani Dayarathna, Himashi Peiris, Kh Tohidul Islam, Tien-Tsin Wong, Zhaolin Chen
arxiv.org/abs/2506.15750

D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI Synthesis
Multi contrast MRI synthesis is inherently challenging due to the complex and nonlinear relationships among different contrasts. Each MRI contrast highlights unique tissue properties, but their complementary information is difficult to exploit due to variations in intensity distributions and contrast specific textures. Existing methods for multi contrast MRI synthesis primarily utilize spatial domain features, which capture localized anatomical structures but struggle to model global intensity …

@arXiv_csCV_bot@mastoxiv.page
2025-06-18 09:07:50

VisText-Mosquito: A Multimodal Dataset and Benchmark for AI-Based Mosquito Breeding Site Detection and Reasoning
Md. Adnanul Islam, Md. Faiyaz Abdullah Sayeedi, Md. Asaduzzaman Shuvo, Muhammad Ziaur Rahman, Shahanur Rahman Bappy, Raiyan Rahman, Swakkhar Shatabda
arxiv.org/abs/2506.14629

VisText-Mosquito: A Multimodal Dataset and Benchmark for AI-Based Mosquito Breeding Site Detection and Reasoning
Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreaks. In this paper, we present VisText-Mosquito, a multimodal dataset that integrates visual and textual data to support automated detection, segmentation, and reasoning for mosquito breeding site analysis. The dataset includes 1,828 annotated images for object detection, 142 images for water surface segmentation, and natural language reasoning texts linked…