“…This vital resource: Contains the technical information and mitigation recommendations for safety and environmental issues related to hydraulic fracturing Offers an historical overview of conventional and unconventional oil and gas drilling Explains the geologic and technical issues associated with fracking of tight sand and shale formulations Presents numerous case studies from the United States EPA and other agencies Discusses issues of co-produced waste water and induced seismicity from the injection of wastewater Written for environmental scientists, geologists, engineers, regulators, city planners, attorneys, foresters, wildlife biologists, and others, Environmental Considerations Associated with Hydraulic Fracturing Operations offers a comprehensive resource to the complex environmental and communication issues related to fracking…”

“…However, to protect cities, which are generally situated at downstream lower elevations, we explore the preservation and restoration of forests at headwater basins and wetlands along rivers from a catchment perspective. …”

“…The Definitive Guide to Drupal 7 was written by the following team of expert Drupal authors: Benjamin Melançon, Jacine Luisi, Károly Négyesi, Greg Anderson, Bojhan Somers, Stéphane Corlosquet, Stefan Freudenberg, Michelle Lauer, Ed Carlevale, Florian Lorétan, Dani Nordin, Ryan Szrama, Susan Stewart, Jake Strawn, Brian Travis, Dan Hakimzadeh, Amye Scavarda, Albert Albala, Allie Micka, Robert Douglass, Robin Monks, Roy Scholten, Peter Wolanin, Kay VanValkenburgh, Greg Stout, Kasey Qynn Dolin, Mike Gifford, Claudina Sarahe, Sam Boyer, and Forest Mars, with contributions from George Cassie, Mike Ryan, Nathaniel Catchpole, and Dmitri Gaskin. …”

“…The natural and the material world--the rivers, forests, and creatures--are sacred and valuable in their own right, not simply for carbon credits or preventing the extinction of one species versus another. …”

“…A close second, however, would be rhesus macaques, who have adapted to-and thrived in-such diverse environments as mountain forests, dry grasslands, and urban sprawl. Scientists have spent countless hours studying these opportunistic monkeys, but rhesus macaques have long been overshadowed in the public eye by the great apes, who, because of their greater intelligence, are naturally assumed to have more to teach us, both about other primates and about humans as well. …”

“…He also dives into a classic result from cooperative game theory called the Shapley values, which has recently been extensively applied to explaining predictions made by nondifferentiable models such as decision trees, random forests, gradient-boosted trees, etc. Time permitting, you'll get a sneak peak of the Fiddler platform and how it incorporates several of these techniques to demystify models. …”

“…During the war, both sides struggled to sustain armies in a northern land of immense forests, vast lakes, and stark seasonal swings in the weather. …”

“…Kurgan maps and theorizes mass graves, incarceration patterns, disappearing forests, and currency flows in a series of cases that range from Kuwait (1991) to Kosovo (1999), New York (2001) to Indonesia (2010).Using digital spatial hardware and software designed for military and governmental use in reconnaissance, secrecy, monitoring, ballistics, the census, and national security, Kurgan engages and confronts the politics and complexities of these technologies and their uses. …”

Gràfic de fulls disponibles a la UdG

“…Inside Ensemble Methods for Machine Learning you will find: Methods for classification, regression, and recommendations Sophisticated off-the-shelf ensemble implementations Random forests, boosting, and gradient boosting Feature engineering and ensemble diversity Interpretability and explainability for ensemble methods Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. …”

“…Inside Ensemble Methods for Machine Learning you will find: Methods for classification, regression, and recommendations Sophisticated off-the-shelf ensemble implementations Random forests, boosting, and gradient boosting Feature engineering and ensemble diversity Interpretability and explainability for ensemble methods Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. …”

“…Se determinó la dinámica de las especies de manglar; índices ecológicos de Shannon y Sörensen, producción forestal y explotación, además del contenido de algunos metales pesados en cada uno de los sitios. …”
Acceso restringido con credenciales UPSA

“…Se determinó la dinámica de las especies de manglar; índices ecológicos de Shannon y Sörensen, producción forestal y explotación, además del contenido de algunos metales pesados en cada uno de los sitios. …”
Enlace del recurso

“…It is organized into 26 excellent chapters which include optical and infrared modeling, microwave scattering propagation, forests and vegetation, soils, ocean temperature, geographic information , object classification, data mining, image processing, passive optical sensor, multispectral and hyperspectral sensing, lidar, radiometer instruments, calibration, active microwave and SAR processing. …”

“…While the measurement of natural capital remains very incomplete, leaving out natural forests, water and soil, the measurement framework can readily be applied to more encompassing data on the natural capital stock, once it becomes available…”

“…Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field…”

“…Laboratory studies add to classical field data informations allowing to replace the megaliths in their environment and to demonstrate the existence of an economic system based upon exchange, ending the myth of autarky inside “the large forest”. This work also analyses modem acculturations of these monuments settled in an area where celtic and arthurian legend is still very much alive…”