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Despite the vital importance of the emerging area of biotechnology and its role in defense planning and policymaking, no definitive book has been written on the topic for the defense policymaker, the military student, and the private-sector bioscientist interested in the "emerging opportunities market" of national security. This edited volume is intended to help close this gap and provide the necessary backdrop for thinking strategically about biology in defense planning and policymaking. This volume is about applications of the biological sciences, here called "biologically inspired innovations," to the military. Rather than treating biology as a series of threats to be dealt with, such innovations generally approach the biological sciences as a set of opportunities for the military to gain strategic advantage over adversaries. These opportunities range from looking at everything from genes to brains, from enhancing human performance to creating renewable energy, from sensing the environment around us to harnessing its power.
This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations
A beloved introductory physics textbook, now including exercises and an answer key, explains the concepts essential for thorough scientific understanding In this concise book, R. Shankar, a well-known physicist and contagiously enthusiastic educator, explains the essential concepts of Newtonian mechanics, special relativity, waves, fluids, thermodynamics, and statistical mechanics. Now in an expanded edition—complete with problem sets and answers for course use or self-study—this work provides an ideal introduction for college-level students of physics, chemistry, and engineering; for AP Physics students; and for general readers interested in advances in the sciences. The book begins at the simplest level, develops the basics, and reinforces fundamentals, ensuring a solid foundation in the principles and methods of physics.
WANT A NON-CODING JOB AT A TECH COMPANY? Interested in product management, marketing, strategy, or business development? The tech industry is the place to be: nontechnical employees at tech companies outnumber their engineering counterparts almost 3 to 1 (Forbes, 2017). You might be worried that your lack of coding skills or tech industry knowledge will hold you back. But here's the secret: you don't need to learn how to code to break into the tech industry. Written by three former Microsoft PMs, Swipe to Unlock gives you a breakdown of the concepts you need to know to crush your interviews, like software development, big data, and internet security. We'll explain how Google's ad targeting algorithm works, but Google probably won't ask you how to explain it in a non-technical interview. But they might ask you how you could increase ad revenue from a particular market segment. And if you know how Google's ad platform works, you'll be in a far stronger position to come up with good growth strategies. We'll show you how Robinhood, an app that lets you trade stocks without commission, makes money by earning interest on the unspent money that users keep in their accounts. No one will ask you to explain this. But if someone asks you to come up with a new monetization strategy for Venmo (which lets you send and receive money without fees), you could pull out the Robinhood anecdote to propose that Venmo earn interest off the money sitting in users' accounts. We'll talk about some business cases like why Microsoft acquired LinkedIn. Microsoft interviewers probably won't ask you about the motive of the purchase, but they might ask you for ideas to improve Microsoft Outlook. From our case study, you'll learn how the Microsoft and LinkedIn ecosystems could work together, which can help you craft creative, impactful answers. You could propose that Outlook use LinkedIn's social graph to give salespeople insights about clients before meeting them. Or you could suggest linking Outlook's organizational tree to LinkedIn to let HR managers analyze their company's hierarchy and figure out what kind of talent they need to add. (We'll further explore both ideas in the book.) Either way, you're sure to impress. Learn the must know concepts of tech from authors who have received job offers for Facebook's Rotational Product Manager, Google's Associate Product Marketing Manager, and Microsoft's Program Manager to get a competitive edge at your interviews!
This book constitutes the refereed post-conference proceedings of the 5th International Conference on Future Access Enablers for Ubiquitous and Intelligent Infrastructures, FABULOUS 2021, held in May 2021. Due to COVID-19 pandemic the conference was held virtually. This year’s conference topic covers security of innovative services and infrastructure in traffic, transport and logistic ecosystems. The 30 revised full papers were carefully reviewed and selected from 60 submissions. The papers are organized in thematic sessions on: Internet of things and smart city; smart environment applications; information and communications technology; smart health applications; sustainable communications and computing infrastructures.
This book presents selected papers from the International Conference on Advances in Materials Processing and Manufacturing Applications (iCADMA 2020), held on November 5–6, 2020, at Malaviya National Institute of Technology, Jaipur, India. iCADMA 2020 proceedings is divided into four topical tracks – Advanced Materials, Materials Manufacturing and Processing, Engineering Optimization and Sustainable Development, and Tribology for Industrial Application.
The International Standard Classification of Occupations 2008 (ISCO-08) is a four-level hierarchically structured classification that covers all jobs in the world. Developed with the benefit of accumulated national and international experience as well as the help of experts from many countries and agencies, ISCO-08 is fully supported by the international community as an accepted standard for international labour statistics. ISCO-08 classifies jobs into 436 unit groups. These unit groups are aggregated into 130 minor groups, 43 sub-major groups and 10 major groups, based on their similarity in terms of the skill level and skill specialisation required for the jobs. This allows the production of relatively detailed internationally comparable data as well as summary information for only 10 groups at the highest level of aggregation. Each group in the classification is designated by a title and code number and is associated with a definition that specifies the scope of the group. The classification is divided into two volumes: Volume I presents the structure and definitions of all groups in ISCO-08 and their correspondence with ISCO-88, which it supersedes, while Volume II provides an updated and expanded index of occupational titles and associated ISCO-08 and ISCO-88 codes.