Shadi Abudalfa,Motaz Saad,Samhaa El-Beltagy
Shadi Abudalfa
A quantum-inspired, biomimetic, and fractal framework for self-healing AI code generation: bridging responsible automation and emergent intelligence [0.03%]
一种量子启发、仿生和分形的自愈AI代码生成框架：连接责任自动化和涌现智能
Mohammadreza Nehzati
Mohammadreza Nehzati
AI-powered code generation systems available today are ill-suited for deployment in agile software development contexts due to various limitations. The paper proposes a self-healing counterpart framework based on quantum-inspired optimizati...
Explainable detection: a transformer-based language modeling approach for Bengali news title classification with comparative explainability analysis using ML and DL [0.03%]
可解释检测：一种基于变压器的语言建模方法，用于孟加拉语新闻标题分类，并通过机器学习和深度学习进行可解释性分析比较
Md Julkar Naeen,Sourav Kumar Das,Sakib Alam Jisan et al.
Md Julkar Naeen et al.
Classifying scattered Bengali text is the primary focus of this study, with an emphasis on explainability in Natural Language Processing (NLP) for low-resource languages. We employed supervised Machine Learning (ML) models as a baseline and...
LegNER: a domain-adapted transformer for legal named entity recognition and text anonymization [0.03%]
基于变压器的法律命名实体识别与文本匿名化方法 LegNER
Ioannis Karamitsos,Nikolaos Roufas,Khalil Al-Hussaeni et al.
Ioannis Karamitsos et al.
The increasing demand for scalable and privacy-preserving processing of legal documents has intensified the need for accurate Named Entity Recognition (NER) systems tailored to the legal domain. In this work, we introduce LegNER, a domain-a...
Implementing federated learning for privacy-preserving emotion detection in educational environments [0.03%]
用于保护隐私的教育环境情绪检测的联邦学习实现方法
Rommel Gutiérrez,William Villegas-Ch,Sergio Luján-Mora
Rommel Gutiérrez
Emotion detection has become an essential tool in educational settings, where understanding and responding to students' emotions is crucial to improving their engagement, academic performance, and emotional well-being. However, traditional ...
Evaluating AI decision tools in Ecuador's courts: efficiency, consistency, and uncertainty in legal judgments [0.03%]
评估厄瓜多尔法院中的AI决策工具：效率、一致性与法律判决的不确定性
Eliana Rodríguez-Salcedo,Carlos Martínez-Bonilla,Betty Pérez-Mayorga et al.
Eliana Rodríguez-Salcedo et al.
This study explores the impact of AI-based decision support tools on judicial performance in Ecuador, a context characterized by institutional uncertainty and procedural inefficiencies. It assesses whether such tools improve efficiency, con...
Enhancing rehabilitation in stroke survivors: a deep learning approach to access upper extremity movement using accelerometry data [0.03%]
基于加速计数据的中风幸存者上肢运动感知的深度学习方法
Tan Tran,Lin-Ching Chang,Peter S Lum
Tan Tran
Upper Extremity (UE) rehabilitation is crucial for stroke survivors, aiming to improve the use of the paretic UE in everyday activities. However, assessing the effectiveness of these treatments is challenging due to a lack of objective meas...
Artificial intelligence for ovarian cancer diagnosis via ultrasound: a systematic review and quantitative assessment of model performance [0.03%]
基于超声的人工智能卵巢癌诊断：系统评价和模型性能量化评估
Igor Garcia-Atutxa,Francisca Villanueva-Flores,Ekaitz Dudagotia Barrio et al.
Igor Garcia-Atutxa et al.
Background: Early and accurate detection of ovarian cancer (OC) remains clinically challenging, prompting exploration of artificial intelligence (AI)-based ultrasound diagnostics. This systematic review and meta-analysis ...
Data-driven pit stop decision support for Formula 1 using deep learning models [0.03%]
基于深度学习模型的F1数据驱动进站决策支持系统
Abhijai Sasikumar,A Anny Leema,P Balakrishnan
Abhijai Sasikumar
In Formula 1, which is among the most competitive motorsports in the world, the timing of a pit stop can make the difference between winning and losing a race. Conventional methods based on human judgment can be erratic, especially in rapid...
Marius Tacke,Matthias Busch,Kevin Linka et al.
Marius Tacke et al.
Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel partitioning algorithm that utilizes competition between mode...