Le travail discipliné : genèse d’un projet technologique au xixe siècle by François Jarrige

“…Face à l’effritement des anciennes régulations du travail, les économistes et les fabricants du début du xixe siècle s’efforcent de trouver des moyens pour lutter contre « l’oppression du travail » et discipliner la main-d’œuvre qui inquiète à l’ère des Révolutions. …”
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An Ensemble Learning Based Intrusion Detection Model for Industrial IoT Security by Mouaad Mohy-Eddine, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

“…IF is exploited to detect and remove outliers from datasets. We apply PCC to choose the most appropriate features. …”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“…However, it faces challenges such as managing complex variables, addressing multicollinearity, handling outliers, ensuring model robustness, and enhancing accuracy, particularly with small to medium-sized datasets. …”
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Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm. by Muhammad Sajid, Kaleem Razzaq Malik, Ali Haider Khan, Sajid Iqbal, Abdullah A Alaulamie, Qazi Mudassar Ilyas

“…The study addresses the difficulties in predicting diabetes precisely from limited labeled data and outliers in diabetes datasets. Furthermore, a thorough food and exercise recommender system is unveiled, offering individualized and health-conscious nutrition recommendations based on user preferences and medical information. …”
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Revolutionizing User Authentication Exploiting Explainable AI and CTGAN-Based Keystroke Dynamics by Hussien Abdel Raouf, Mostafa M. Fouda, Mohamed I. Ibrahem

“…We first use quantile transformation (QT) to mitigate outliers in the user's typing behavior that affects the authentication process and then employ conditional tabular generative adversarial networks (CTGAN) for data augmentation to learn the users' typing patterns better. …”
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Collection, Collation, and Comparison of 3D Coronal CME Reconstructions by C. Kay, E. Palmerio

“…These remain the most probable values over the solar cycle, though we find more extreme outliers in the deviation toward solar maximum.…”
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Cybersecurity Practices and Supply Chain Performance: The Case of Jordanian Banks by Saleh Fahed Al-Khatib, Yara Yousef Ibrahim, Mohammad Alnadi

“…Data from 40 managers’ and 250 digital banking customers’ surveys were collected, of which 220 were valid to be analyzed using IBM SPSS V26 and PLS-SEM V4; 30 responses were excluded due to invalidity issues such as zero standard deviation and outliers identified using Cook’s distance. This study empirically demonstrates the significant positive impact of cybersecurity practices on Jordanian banking supply chain performance. …”
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Consistent movement of viewers' facial keypoints while watching emotionally evocative videos. by Shivansh Chandra Tripathi, Rahul Garg

“…The simplicity of recording facial expressions with the automated Average t-statistic expands the applications of CRM such as measuring engagement in online learning, customer interactions, etc., and diagnosing outliers in healthcare conditions like stroke, autism, depression, etc. …”
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PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations by Fahmida Khanom, Mohammad Shorif Uddin, Rafid Mostafiz

“…Comprehensive data preparation included encoding categorical features, imputing missing values, removing outliers, addressing data imbalance, scaling data, selecting relevant features, and so on. …”
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A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy by Chetan Shetty, S. Seema, B. J. Sowmya, Rajesh Nandalike, S. Supreeth, Dayananda P., Rohith S., Vishwanath Y., Rajeev Ranjan, Venugopal Goud

“…It is not only capable of finding clusters of various sizes and shapes but can also detect outliers. DBSCAN takes in two important input parameters—Epsilon (Eps) and Minimum Points (MinPts). …”
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Establishing Normative Values for Inter-Limb Kinetic Symmetry During Landing in Uninjured Adolescent Athletes by Adam W. VanZile, David M. Reineke, Matthew J. Snyder, Daniel D. Jones, Renee L. Dade, Thomas G. Almonroeder

“… # Results Measures of central tendency, variability, percentiles, and outliers were calculated/identified based on the uninjured athletes’ symmetry indices. …”
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Polygenic burden of short tandem repeat expansions promotes risk for Alzheimer’s disease by Michael H. Guo, Wan-Ping Lee, Badri Vardarajan, Gerard D. Schellenberg, Jennifer E. Phillips-Cremins

“…We implement an approach to identify STR expansions as STRs with tract lengths that are outliers from the population. We then test for differences in aggregate burden of expansions in case versus control individuals. …”
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Self-Adaptive K-Means Based on a Covering Algorithm by Yiwen Zhang, Yuanyuan Zhou, Xing Guo, Jintao Wu, Qiang He, Xiao Liu, Yun Yang

“…However, the value of the clustering number k in the K-means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved K-means clustering algorithm called the covering K-means algorithm (C-K-means). …”
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Predicting occupational musculoskeletal disorders in South Korean male office workers using a robust and sparse twin support vector machine by Haewon Byeon

“…The RSTSVM model demonstrated superior performance in predicting MSDs, with an Area under the Receiver Operating Characteristic Curve (AUC-ROC) value of 0.84, effectively managing high-dimensional data and maintaining robustness against outliers and noise. Furthermore, the RSTSVM model provided enhanced interpretability, making it easier to identify and understand key risk factors compared to traditional models. …”
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GPS TRAJECTORY CLUSTERING FOR SPATIO – TEMPORAL BEHAVIOR ANALYSIS: THE APPLICATION OF HEATMAP TECHNIQUES AND SPATIO- TEMPORAL DUAL GRAPH NEURAL NETWORK by Mais Muhanad, Wadhah R.Baiee

“…Numerous measures are taken to boost the clustering accuracy of the applied techniques, including addressing missing values and outliers. Additionally, this thesis introduces a framework for time estimation based on graph-based deep learning, termed Spatio-Temporal Dual Graph Neural II Networks (STDGNN). …”
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Diffusion Partition Consensus: Diffusion-Aided Time-of-Flight Estimates, Anomaly Detection, and Localization for Ultrasonic Nondestructive Evaluation Data by Nick Torenvliet, John S. Zelek

“…Diffusion partition consensus is a novel generative AI-based technique for time-series anomaly detection and data imputation in the presence of outliers. To illustrate the method, an implementation with design choices tailored for well-structured time series typical of single probe ultrasonic nondestructive evaluation (NDE) datasets is proposed. …”
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Adaptive Gaussian Incremental Expectation Stadium Parameter Estimation Algorithm for Sports Video Analysis by Lizhi Geng

“…The sparse generative model is constructed by combining L1 regularization and subspace representation, which retains sufficient representational power while dealing with outliers. To overcome the shortcomings of the traditional multiplicative fusion mechanism, this paper proposes an adaptive selection mechanism based on Euclidean distance, which aims to detect deteriorating models in time during the dynamic tracking process and adopt corresponding strategies to construct more reasonable likelihood functions. …”
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Dynamic Stabilization for Challenging Lumbar Degenerative Diseases of the Spine: A Review of the Literature by Tuncay Kaner, Ali Fahir Ozer

“…This paper evaluates the dynamic stabilization of the lumbar spine and talks about chronologically some novel dynamic stabilization devices and thier efficacies.…”
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Well-Production Forecasting Using Machine Learning with Feature Selection and Automatic Hyperparameter Optimization by Ruibin Zhu, Ning Li, Yongqiang Duan, Gaofeng Li, Guohua Liu, Fengjiao Qu, Changjun Long, Xin Wang, Qinzhuo Liao, Gensheng Li

“…This research focuses on the geological, engineering, and production data of 435 fracturing wells in the North China Oilfield. First, outliers were detected, and missing values were handled using the mean imputation and nearest neighbor methods. …”
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Population genetics of Glossina fuscipes fuscipes from southern Chad by Ravel, Sophie, Mahamat, Mahamat Hissène, Ségard, Adeline, Argilés-Herrero, Rafael, Bouyer, Jérémy, Rayaisse, Jean-Baptiste, Solano, Philippe, Guihini Mollo, Brahim, Pèka, Mallaye, Darnas, Justin, Belem, Adrien Marie Gaston, Yoni, Wilfrid, Noûs, Camille, De Meeûs, Thierry

“…The long-range dispersal and the existence of genetic outliers suggest a possibility of migration from remote sites such as the Central African Republic in the south (although the fly situation remains unknown there) and/or a genetic signature of recent exchanges. …”
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