MACHINE LEARNING APPROACHES TO PREDICT AND DETECT EARLY-ONSET OF DIGITAL DERMATITIS IN DAIRY COWS USING SENSOR DATA

Machine learning approaches to predict and detect early-onset of digital dermatitis in dairy cows using sensor data

The present study aimed to employ machine learning algorithms based on sensor behavior data for (1) early-onset detection of digital dermatitis (DD) and (2) DD prediction in dairy cows.Our machine learning model, which was based on the Tree-Based Pipeline Optimization Tool (TPOT) automatic machine learning method, Spotlights for DD detection on day

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Investigating and Comparing the Relationship between Entrepreneurial Characteristics of Organizational Personnel (Male & Female) and Their Job Satisfaction

Abstract The present study was conducted to investigate and compare the relationship between entrepreneurial characteristics and job satisfaction among male and female participant nurses.The study population consisted of the nurses working at the Kamyab Hospital in the city of Mashhad.After the collection and analysis of the data, 12 hypotheses Out

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Improved Classification Models to Distinguish Natural from Anthropic Oil Slicks in the Gulf of Mexico: Seasonality and Radarsat-2 Beam Mode Effects under a Machine Learning Approach

Distinguishing between natural and anthropic oil slicks is a challenging task, especially in the Gulf of Mexico, where these events can be simultaneously observed and recognized as seeps or spills.In this study, a powerful data analysis provided by machine learning (ML) methods was employed to develop, test, and implement a classification model (CM

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Multicriteria Decision Model to Support the Evaluation of Common Jurisdiction Violence in the Capital Cities of the States of Mexico

The capital cities of the states of the Mexican Republic present a considerable heterogeneity in terms of their level of Outdoor Rocking Lounge Chair public security, so their correct characterization is an essential requirement, but not sufficient, for the elaboration of public policies for the prevention of crimes in the common jurisdiction.In th

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