Kam Tem

Anthology featuring over 20 Indigenous authors who are revered in their communities. These are their testimonies.

Scores of talented and dedicated people serve the forensic science community, performing vitally important work. However, they are often constrained by lack of adequate resources, sound policies, and national support. It is clear that change and advancements, both systematic and scientific, are needed in a number of forensic science disciplines to ensure the reliability of work, establish enforceable standards, and promote best practices with consistent application. Strengthening Forensic Science in the United States: A Path Forward provides a detailed plan for addressing these needs and suggests the creation of a new government entity, the National Institute of Forensic Science, to establish and enforce standards within the forensic science community. The benefits of improving and regulating the forensic science disciplines are clear: assisting law enforcement officials, enhancing homeland security, and reducing the risk of wrongful conviction and exoneration. Strengthening Forensic Science in the United States gives a full account of what is needed to advance the forensic science disciplines, including upgrading of systems and organizational structures, better training, widespread adoption of uniform and enforceable best practices, and mandatory certification and accreditation programs. While this book provides an essential call-to-action for congress and policy makers, it also serves as a vital tool for law enforcement agencies, criminal prosecutors and attorneys, and forensic science educators.

Rogue artificial intelligence and a lethal resource crisis threaten an asteroid colony--with an organized crime syndicate pulling the strings. Compulsively readable and packed with challenging ideas . . .--"Publishers Weekly," starred review.

The first in a sweeping and action-packed debut fantasy duology loosely inspired by the early climbers of Mt. Everest—perfect for fans of Cindy Pon and Alison Goodman. Kamzin has always dreamed of becoming one of the Emperor’s royal explorers, the elite climbers tasked with mapping the wintry, mountainous Empire and spying on its enemies. She knows she could be the best in the world, if only someone would give her a chance. But everything changes when the mysterious and eccentric River Shara, the greatest explorer ever known, arrives in her village and demands to hire Kamzin—not her older sister Lusha, as everyone had expected—for his next expedition. This is Kamzin’s chance to prove herself—even though River’s mission to retrieve a rare talisman for the emperor means climbing Raksha, the tallest and deadliest mountain in the Aryas. Then Lusha sets off on her own mission to Raksha with a rival explorer who is determined to best River, and Kamzin must decide what’s most important to her: protecting her sister from the countless perils of the climb or beating her to the summit. The challenges of climbing Raksha are unlike anything Kamzin expected—or prepared for—with avalanches, ice chasms, ghosts, and even worse at every turn. And as dark secrets are revealed, Kamzin must unravel the truth of their mission and of her companions—while surviving the deadliest climb she has ever faced.

This is a comprehensive guide to learning about a wonderful technique called mind maps. Mind maps are an amazing organizational and creativity tool that can improve memory, concentration, communication, organization, creativity, and time management. This book is the ultimate resource on the topic of mind maps. In a short time, it can enhance your skills in reading, writing, learning, note taking, brainstorming, planning, productivity, and so much more.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Prepared especially to meet the needs of the American student who wishes to read Thai newspapers and other Thai source materials.