This paper proposes a novel approach suitable to design energy-efficient approximate multipliers using both ASIC and FPGAs. The new strategy harnesses specific encoding logics based on bit significance computes the product performing accurate sub-multiplications by applying an unconventional instead of computational modules implementing traditional static or dynamic bit-truncation approaches. p...

Abstract Mechanical manufacturing industry consumes substantial energy with low efficiency. Increasing pressures from price and environmental directive force mechanical industries to implement efficient technologies for reducing consumption improving efficiency of their machining processes. In a practical process, cutting parameters are vital variables set by manufacturers in accordance require...

Solar power is the major renewable energy source opted by developing countries as stand-alone / Grid enabled system. Industries and educational institutions are opting for solar energy to combat power crisis. This paper proposes knowledge based, self configurable, smart controller to efficiently use solar energy according to load, under frequent grid failure environment. It is enabled with faul...

Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the...

The term efficient use of energy includes all the technical and economical measures aimed at reducing the specific energy demand of a production system or economic sector. Although implementation of energy-saving techniques may require initial investments, short-term financial returns can often be achieved through lower fuel costs due to the reduced energy demand. Improving the use of energy is...

3 Energy Metrics and Cost Models 7 3.1 Node Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.1 Node Cost in Source-based Multicast Tree . . . . . . . . . . . . . 9 3.1.2 Node Cost in Group-shared Multicast Tree . . . . . . . . . . . . 10 3.2 Multicast Tree Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.1 Minimizing Energy Consumption: . . . ....