Algorithmic Bias as a Core Legal Dilemma in the Age of Artificial Intelligence: Conceptual Basis and the Current State of Regulation by Gergely Ferenc Lendvai, Gergely Gosztonyi

“…We employed comparative legal analysis and reviewed pertinent regulatory documents to examine how the fragmented U.S. approaches and the EU’s user-centric legal frameworks, such as the GDPR, DSA, and AI Act, address the systemic risks posed by biased algorithms. The findings underscore persistent enforcement gaps, particularly concerning opaque black-box algorithmic design, which hampers bias detection and remediation. …”
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calibrar: An R package for fitting complex ecological models by Ricardo Oliveros‐Ramos, Yunne‐Jai Shin

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Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

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A Differential-Evolution-Based Approach to Extract Univariate Decision Trees From Black-Box Models Using Tabular Data by Rafael Rivera-Lopez, Hector G. Ceballos

“…To tackle this issue, we propose an evolutionary approach to induce univariate decision trees that accurately mimic the behavior of black-box models using tabular data. Our method employs two differential evolution algorithm variants, focusing on building univariate decision trees to enhance model explainability. …”
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New approaches for capturing and estimating variation in complex animal color patterns from digital photographs: application to the Eastern Box Turtle (Terrapene carolina) by Erik Maki, Tilmann Glimm, Paramahansa Pramanik, Ylenia Chiari, Maria Kiskowski

“…In this study, we developed algorithms to capture and obtain data on 19 different pattern measurements from digital images of 55 individuals of the Eastern box turtle Terrapene carolina sampled in the field and in a museum. …”
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Explainable Supervised Learning Models for Aviation Predictions in Australia by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…Given the safety-critical nature of aviation, the lack of transparency in AI-generated predictions poses significant challenges for industry stakeholders. …”
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An Iterative Optimization Algorithm for Planning Spacecraft Pathways Through Asteroids by Valentino Santucci

“…In this article, we explore the use of meta-heuristic algorithms for costly black-box permutation optimization problems. …”
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La Inteligencia Artificial en la educación: Big data, cajas negras y solucionismo tecnológico / Artificial Intelligence in Education: Big Data, Black Boxes, and Technological Solut... by Xavier Giró-Gracia, Juana María Sancho-Gil

“…This article, geared towards educators, academics in the field of Education, and policymakers, first introduces the concepts of ‘Big Data’, Artificial Intelligence, Machine Learning algorithms and how they are presented and deployed as ‘black boxes’, and the possible impact on education these new software solutions can have. …”
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An Advanced Dynamic Framed-Slotted ALOHA Algorithm Based on Bayesian Estimation and Probability Response by Chaowei Wang, Menglong Li, Juyi Qiao, Weidong Wang, Xiuhua Li

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On the practical, ethical, and legal necessity of clinical Artificial Intelligence explainability: an examination of key arguments by Justin Blackman, Richard Veerapen

“…While the use of autonomous black box algorithms is compellingly discouraged, the same cannot be said for the whole of medical artificial intelligence technologies that lack explainability. …”
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A Deep Learning Segmentation Model for Detection of Active Proliferative Diabetic Retinopathy by Sebastian Dinesen, Marianne G. Schou, Christoffer V. Hedegaard, Yousif Subhi, Thiusius R. Savarimuthu, Tunde Peto, Jakob K. H. Andersen, Jakob Grauslund

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Enhancing 5G Vehicular Edge Computing Efficiency with the Hungarian Algorithm for Optimal Task Offloading by Mohamed Kamel Benbraika, Okba Kraa, Yassine Himeur, Khaled Telli, Shadi Atalla, Wathiq Mansoor

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Application of Lightweight Target Detection Algorithm Based on YOLOv8 for Police Intelligent Moving Targets by Yanjie Zhang, Xiaojun Liu, Yuehan Shi, Zecong Ding, Xiaoming Zhang

“…The police intelligent moving target must deploy target detection algorithms on the hardware platform, but the traditional you only look once (YOLO)v8 algorithm has a large framework, which will slow recognition due to the hardware platform’s lack of arithmetic power. …”
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Survivor detection approach for post earthquake search and rescue missions based on deep learning inspired algorithms by Rajendrasinh Jadeja, Tapankumar Trivedi, Jaymit Surve

“…This paper presents a novel approach to survivor detection using a snake robot equipped with deep learning (DL) based object identification algorithms. We evaluated the performance of three main algorithms: Faster R-CNN, Single Shot MultiBox Detector (SSD), and You Only Look Once (YOLO). …”
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Toward Sustainable Campus Energy Management: A Comprehensive Review of Energy Management, Predictive Algorithms, and Recommendations by Noor Islam Jasim, Saraswathy Shamini Gunasekaran, Nouar AlDahoul, Ali Najah Ahmed, Ahmed El-Shafie, Mohsen Sherif, Moamin A Mahmoud

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PFARN: Pyramid Fusion Attention and Refinement Network for Multiscale Ship Detection in SAR Images by Ke Li, Hang Yu, Suqi Li, Shanhu Chen, Bailu Wang

“…Third, a more suitable central loss function is used for the detection head to ensure that the bounding box flexibly adapts to the size and location of the object. …”
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Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms by Leta Daba Gemechu, Dame Alemayehu Efa, Robsan Abebe

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Progressive noise photons removal from ICESAT-2 data based on the characteristics of different types of noise by Zhenyang Hui, Li Zhang, Shuanggen Jin, Wenbo Chen, Penggen Cheng, Yao Yevenyo Ziggah

“…Existing methods for noise photon removal often struggle with parameter tuning, lack robustness, and may compromise accuracy across different datasets. …”
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Machine learning-based prediction of CO2 solubility in methyldiethanolamine solutions: A comparative study by Sajjad Fazeli, Mohammad Amin Moradkhani, Behrouz Bayati

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Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

“…This lack of interpretability limits their clinical trust and adoption. …”
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