Software for Arabic Machine Printed Optical Character Recognition (MACRS) by Mahdi Al- Obaidi, Laheeb Ibrahim

“…Machine printed Arabic Character Recognition System (MACRS] is concerned with recognition of machine printed alphanumeric Arabic characters. …”
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Tooth Cutting Machining of Cycloid Coupling based on Monolithic Cutter by Zhiyong Wang, Wenhao Yu, Ying Zhang, Yiyu Zeng

“…Through the use of monolithic cutter to process the cycloid coupling on domestic CNC bevel gear cutting machine，the correctness and feasibility of cutting principle and processing method is verified by tooth profile error measurement and contact pattern inspection.…”
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STATISTICAL STUDY ON PROFILE DEVIATIONS OF CYLINDER GRINDING MACHINE RACEWAYS by Mikhail Y. Shcherba, Vadim A. Kokhanovskiy

“…The statistical analysis of the deviations of the outer and inner bearing race profiles of the cylinder grinding machines is resulted. The patterns of forming vibration spectra of the bearings of the same series and standard size, which designate the option of the practical recommendations on reducing noise levels of the bearing units, are deduced.…”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…As environmental sciences increasingly rely on complex datasets, machine learning (ML) has become crucial for identifying patterns and relationships. …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…Initially, experimental data are generated by systematically varying key AM parameters, layer height, infill density, infill pattern, build orientation, and number of shells. …”
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Experimental studies on noise and vibration spectra of copy milling machines by Sergey V. Golosnoy, Alexander N. Chukarin

“…The research objective is to study the development of the noise spectra patterns in the operating area of copy mill operators. …”
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The Extreme Value Support Measure Machine for Group Anomaly Detection by Lixuan An, Bernard De Baets, Stijn Luca

“…Group anomaly detection is a subfield of pattern recognition that aims at detecting anomalous groups rather than individual anomalous points. …”
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An Overview and Classification of Machine Learning Approaches for Radar Signal Deinterleaving by Louis Lesieur, Jean-Marc Le Caillec, Ali Khenchaf, Vincent Guardia, Abdelmalek Toumi

“…To this end, we identify some criteria to characterize a method: its used technique, underlying assumptions, exploited parameters, input characterization, and architectural pattern. First, the problem of RSD is detailed with its challenges and operational requirements. …”
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A Machine Learning Approach for the Prediction of Thermostable β-Glucosidases by Diego Mariano

“…I hypothesize that the signature model proposed here can help understand the structural patterns in thermostable enzymes and shed light on the design of more efficient enzymes for biofuel production.…”
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Anomaly detection research using Isolation Forest in Machine Learning by A. S. Kechedzhiev, O. L. Tsvetkova

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Machine Learning Optimization and Challenges in Used Car Price Prediction by Zheng Yufan

“…To begin with, models like XGBoost and Random Forest excel at processing large-scale data and identifying complex feature patterns, thanks to their ability to use an ensemble of decision trees to reduce bias and variance. …”
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Optimize building energy efficiency design and evaluation with machine learning by Chun Gu

“…By comprehensively analyzing energy consumption data, environmental factors, building characteristics, and user behavior patterns, this paper proposes a machine learning-based approach aimed at accurately predicting and improving the energy efficiency of buildings. …”
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MACHINE LEARNING AND ECONOMETRICS: BRIDGING THE GAP FOR ENHANCED ECONOMIC ANALYSIS by Jamiu Adeniyi Yusuf, Abdulkadri IDRIS, Azeez Olawale AKINLOLU

“…It illustrates how deep learning models, like neural networks, improve forecasting accuracy by capturing complex patterns in time series data. In causal analysis, machine learning techniques such as random forests and generalized random forests enhance estimation of treatment effects, enabling robust policy evaluation. …”
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Physics-Informed Machine Learning for Power Grid Frequency Modeling by Johannes Kruse, Eike Cramer, Benjamin Schäfer, Dirk Witthaut

“…Social behavior determines load patterns, electricity markets regulate the generation, and weather-dependent renewables introduce power fluctuations. …”
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Phyloreferences: Tree-Native, Reproducible, and Machine-Interpretable Taxon Concepts by Hilmar Lapp, Nico Cellinese, Stijn Conix

“…To fully take advantage of this wealth of data to discover and understand large-scale evolutionary and ecological patterns, computational data integration, i.e., the use of machines to link data at large scale, is crucial. …”
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From Words to Ratings: Machine Learning and NLP for Wine Reviews by Iliana Ilieva, Margarita Terziyska, Teofana Dimitrova

“…The present study aims to show how natural language processing (NLP) and machine learning methods can be applied to analyze expert-written Bulgarian wine descriptions and to extract patterns related to wine quality and style. …”
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Integrating Machine Learning and IoT for Effective Plant Disease Management by Bhoi Manjulata, Dubey Ahilya

“…Machine learning (ML) and Internet of Things (IoT) are bolting down the agriculture in the area of plant disease management, especially. …”
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Non-Invasive Biomarkers in the Era of Big Data and Machine Learning by Konstantinos Lazaros, Styliani Adam, Marios G. Krokidis, Themis Exarchos, Panagiotis Vlamos, Aristidis G. Vrahatis

“…Computational advancements, particularly in artificial intelligence and machine learning, are addressing these limitations by uncovering complex patterns in multi-modal datasets, enhancing diagnostic accuracy and facilitating personalized medicine. …”
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BLE Signal Processing and Machine Learning for Indoor Behavior Classification by Yi-Shiun Lee, Yong-Yi Fanjiang, Chi-Huang Hung, Yung-Shiang Huang

“…The results show that the proposed system reliably tracks user locations and identifies behavior patterns. This research supports elderly care, remote health monitoring, and non-invasive behavior analysis, providing a privacy-preserving solution for smart healthcare applications.…”
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Detection of Cisplatin Resistance in Bladder Cancer Using Machine Learning by Moditha Reddy Jagannatha Reddy, Mrudula Ranganatha, Shanthala Lakshminarayana, Jayoung Kim, Sungyong Jung, Yuze Sun, Hyusim Park

“…This work provides valuable insights into the role of methylation patterns in BC recurrence and offers potential for personalized therapeutic strategies aimed at overcoming cisplatin resistance and improving clinical outcomes.…”
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