Common Pines of Florida by Niels Proctor, Martha C. Monroe

“…Written by Niels Proctor and Martha Monroe, and published by the School of Forest Resources and Conservation, April 2016. FOR21/FR003: Common Pines of Florida (ufl.edu) …”
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Leucaena leucocephala, White Leadtree by Michael G. Andreu, Melissa H. Friedman, Robert J. Northrop

“…Northrop, and published by the UF Department of School of Forest Resources and Conservation, July 2012. FOR299/FR367: Leucaena leucocephala, White Leadtree (ufl.edu) …”
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Tung Oil Production in Florida by Patrick Joseph Minogue

“…This 3-page fact sheet written by Pat Minogue and published by the UF/IFAS School of Forest Resources and Conservation presents a history of tung oil production in Florida and provides the ecology and cultivation of the fast-growing trees. …”
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Perancangan Aplikasi Tanggap Api Berbasis Android Menggunakan Metode Design Sprint by Agus Tedyyana, Muhammad Fauzi, Depandi Enda, Fajar Ratnawati, Elgamar Syam

“…Throughout 2019, at least 209 forest and land fire disasters occurred with a burned area of around 2146,2 Ha. …”
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Model Klasifikasi Dengan Logistic Regression Dan Recursive Feature Elimination Pada Data Tidak Seimbang by Sutarman, Rimbun Siringoringo, Dedy Arisandi, Edi Kurniawan, Erna Budhiarti Nababan

“…These results are better than those of four other classification models, namely Naïve Bayes, Decision Tree, K-NN, and Random Forest. …”
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Desain Penilaian Risiko Privasi pada Aplikasi Seluler Melalui Model Machine Learning Berbasis Ensemble Learning dan Multiple Application Attributes by R. Ahmad Imanullah Zakariya, Kalamullah Ramli

“…Hasil percobaan menunjukkan bahwa penerapan ensemble learning dengan algoritma klasifikasi Decision Tree (DT), K-Nearest Neighbor (KNN), dan Random Forest (RF) memiliki performa model yang lebih baik dibandingkan dengan menggunakan algoritma klasifikasi tunggal, dengan accuracy sebesar 95.2%, nilai precision 93.2%, nilai F1-score 92.4%, dan True Negative Rate (TNR) sebesar 97.6%. …”
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Spatiotemporal variation and influencing factors of phosphorus in Asia’s longest river based on receptor model and machine learning by Gege Cai, Jiamei Zhang, Wanlu Li, Jiejun Zhang, Yun Liu, Shanshan Xi, Guolian Li, Haibin Li, Xing Chen, Fanhao Song, Fazhi Xie

“…Machine learning models (e.g., RidgeCV, Random Forest, XGBoost) were used to establish a connection between total phosphorus concentrations and explanatory variables defining influencing factors, aiming to predict total phosphorus concentrations in the Yangtze River. …”
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Differences in pyrolysis behavior and volatiles of tar-rich coal with various origins by Qingmin Shi, Xinyue Zhao, Shuangming Wang, Hongchao Zhao, Ruijun Ji, Chunhao Li, Bingyang Kou, Jun Zhao

“…For low-temperature pyrolysis experiments, three coal-forming environments were selected: limno-telmatic (Sample S-1), wet forest swamp (Sample O-1), and dry forest swamp (Sample O-2). …”
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Addressing Misconceptions about Wildland-Urban Interface Issues by Martha C. Monroe

“…This document is FOR 108, one of a series of the School of Forest Resources and Conservation Department, UF/IFAS Extension. …”
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Geosmithia Species in Florida: Common Fungal Symbionts of Wood-Boring Bark Beetles by Yin-Tse Huang, Jiri Hulcr

“…This 4-page fact sheet written by Yin-Tse Huang and Jiri Hulcr and published by the UF/IFAS School of Forest Resources and Conservation provides basic guidelines to sample Geosmithia species in the field and information for distinguishing the plant pathogenic Geosmithia morbida from other Geosmithia species. …”
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Teach Aquaculture Curriculum: What Makes a Good Fish Food? by Craig S. Kasper, Cortney L. Ohs, Brian E. Myers, Frank A. Chapman, Amber L. Garr, R. Leroy Creswell, Carlos V. Martinez, Elisa J. Livengood

“…Published by the UF School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, July 2010. …”
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FRAGSTATS: A Free Tool for Quantifying and Evaluating Spatial Patterns by Benxin Chen, Basil V. Iannone III

“…Iannone III and published by the UF/IFAS School of Forest Resources and Conservation introduces one such resource, a free software called FRAGSTATS. …”
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Molluscan Shellfish Aquaculture and Production by Huiping Yang, Leslie N. Sturmer, Shirley Baker

“…Sturmer, and Shirley Baker, and published by the UF School of Forest, Fisheries, and Geomatics Sciences, January 2016. …”
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Ecogeographical Amplitude and Habitat of Two Species of the Genus- <i>Terminalia</i> (Combretaceae) In the Central Niger Delta Areas in Rivers State by NL Edwin-Wosu, T Omara-Achong, BL Nyannanyo

“…Terminalia ivorensis does occur wildly and in abundant in the forest than T. catappa, which is frequently cultivated around homes and residential areas, though occurred more in fresh water ecozone. …”
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Teach Aquaculture Curriculum: How Big Is That Pond? by Cortney L. Ohs, Amber L. Garr, R. Leroy Creswell, Elisa J. Livengood, Brian E. Myers, Carlos V. Martinez, Frank A. Chapman, Craig S. Kasper

“…Published by the UF School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, May 2010. …”
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Teach Aquaculture Curriculum: Spawning and Rearing Bivalve Molluscs--Larval Culture by R. Leroy Creswell, Cortney L. Ohs, Craig S. Kasper, Carlos V. Martinez, Elisa J. Livengood, Amber L. Garr, Frank A. Chapman, Brian E. Myers

“…Published by the UF School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, July 2010. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…Some of the most commonly used machine learning algorithms for this issue are Logistic Regression, Gaussian Naive Bayes, Bernoulli Naive Bayes, Decision Tree, and Random Forest. …”
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Teach Aquaculture Curriculum: Introduction by Cortney L. Ohs, R. Leroy Creswell, Amber L. Garr, Carlos V. Martinez, Brian E. Myers, Elisa J. Livengood, Craig S. Kasper, Frank A. Chapman

“…Published by the UF School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, July 2010. …”
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Lessons Learned from Evaluations of Citizen Science Programs by Luke Gommerman, Martha C. Monroe

“…Monroe, and published by the UF Department of School of Forest Resources and Conservation, May 2012. FOR291/FR359: Lessons Learned from Evaluations of Citizen Science Programs (ufl.edu) …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…Some of the most commonly used machine learning algorithms for this issue are Logistic Regression, Gaussian Naive Bayes, Bernoulli Naive Bayes, Decision Tree, and Random Forest. …”
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