An investigation into adaptive power reduction techniques for neural hardware

In light of the growing applicability of Artificial Neural Network (ANN) in the signal processing field [1] and the present thrust of the semiconductor industry towards lowpower SOCs for mobile devices [2], the power consumption of ANN hardware has become a very important implementation issue. Adaptability is a powerful and useful feature of neural networks. All current approaches for low-power ANN hardware techniques are ‘non-adaptive’ with respect to the power consumption of the network (i.e. power-reduction is not an objective of the adaptation/learning process). In the research work presented in this thesis, investigations on possible adaptive power reduction techniques have been carried out, which attempt to exploit the adaptability of neural networks in order to reduce the power consumption. Three separate approaches for such adaptive power reduction are proposed: adaptation of size, adaptation of network weights and adaptation of calculation precision. Initial case studies exhibit promising results with significantpower reduction

Aeronautical engineering: A continuing bibliography with indexes (supplement 322)

This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in Oct. 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Proceedings of the 2nd Energy Security and Chemical Engineering Congress

Mechanical engineering is a field that is continuously evolving as a profession to provide sustainable design, products and technologies for society. Mechanical engineering products, in conjunction with technological advances in other sectors, contribute to noise, water and air pollution, and the degradation of land and landscape. The rate of production, both energy and products, is increasing at such a rapid rate that natural regeneration can no longer sustain. Emission control is a fast-growing topic for mechanical engineers and others, encompassing the development of machines and processes that produce fewer pollutants as well as new materials and processes that can decrease or eliminate pollution that has already been generated. And, in an increasingly environmentally conscious world, the concept of sustainability is also intrinsically important to the success or failure of any engineering product or processes. Mechanical engineers thus play a central role in applying a truly modern approach for enabling the global transition to green energy and sustainable prac-tices. To address climate change, researchers are progressively looking into a wide range of novel solutions for energy conversion, engine efficiency, alternative fuels, nature-inspired materials, enhanced manufacturing processes and so on. In this context, this book presents part of the proceedings of the Mechanical and Materials track of the 2nd Energy Security and Chemical Engineering Congress (ESChE 2021) as presented by the academics, researchers and postgraduate students. The book provides insights into different aspects of mechanical processes, nanoma-terials and alternate fuels that set the stage for development of sustainable techno-logical solutions. The content of this book will be useful for students, researchers and professionals working in the areas of mechanical engineering, materials, energy technologies, optimization and allied fields

Idaho National Laboratory LDRD Annual Report FY 2012

This report provides a glimpse into our diverse research and development portfolio, wwhich encompasses both advanced nuclear science and technology and underlying technologies. IN keeping with the mission, INL's LDRD program fosters technical capabilities necessary to support current and future DOE-Office of Nuclear Energy research and development needs

Additive Manufacturing of Bio and Synthetic Polymers

Additive manufacturing technology offers the ability to produce personalized products with lower development costs, shorter lead times, less energy consumed during manufacturing and less material waste. It can be used to manufacture complex parts and enables manufacturers to reduce their inventory, make products on-demand, create smaller and localized manufacturing environments, and even reduce supply chains. Additive manufacturing (AM), also known as fabricating three-dimensional (3D) and four-dimensional (4D) components, refers to processes that allow for the direct fabrication of physical products from computer-aided design (CAD) models through the repetitious deposition of material layers. Compared with traditional manufacturing processes, AM allows the production of customized parts from bio- and synthetic polymers without the need for molds or machining typical for conventional formative and subtractive fabrication.In this Special Issue, we aimed to capture the cutting-edge state-of-the-art research pertaining to advancing the additive manufacturing of polymeric materials. The topic themes include advanced polymeric material development, processing parameter optimization, characterization techniques, structure–property relationships, process modelling, etc., specifically for AM

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

NASA University program management information system, FY 1993

The University Program Report, Fiscal Year 1993, provides current information and related statistics for 7682 grants/contracts/cooperative agreements active during the report period. NASA field centers and certain Headquarters program offices provide funds for those R&D activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program

NASA university program management information system, FY 1994

The University Program report, Fiscal Year 1994, provides current information and related statistics for 7841 grants/contracts/cooperative agreements active during the reporting period. NASA field centers and certain Headquarters program offices provide funds for those activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program