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The Fundamentals of Geometric Dimensioning and Tolerancing 2018 Using Critical Thinking Skills by Alex Krulikowski reflects the technical content found in the latest release of the ASME Y14.5-2018 Standard. This book includes several key features that aid in the understanding of geometric tolerancing. Each of the textbook's 26 chapters focuses on a major topic that must be mastered to be fluent in the fundamentals of GD&T. Each topic includes a goal that is defined and supported by a set of performance objectives that include real-world examples, verification principles and methods, and chapter summaries. There are more than 260 performance objectives that describe specific, observable, measurable actions that the student must accomplish to demonstrate mastery of each goal. Learning is reinforced by completing three types of exercise problems, along with critical thinking questions that promote application of GD&T on the job.

Why should the supply chain be concerned if their buyers or subcontractors are purchasing counterfeit electronic parts or if their products contain counterfeit electronic parts? If these parts end up in items that are safety critical and security-risk sensitive such as aviation, space, and defense products, whole secure systems can be comprised. As organizations have become aware of counterfeit parts, one of their responses may be to test upon acceptance or prior to receipt. But testing alone may not detect all counterfeits. Possible sources of counterfeits include products that did not meet quality control requirements and were not destroyed, overruns sold into the market place, unauthorized production shifts, theft, and e-waste. The counterfeited electronic part ends up in the supply chain when ordered by an unsuspecting buyer, who does not confirm the originating source of the part.

This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs―with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial deep-learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs.