A first-principles approach to magnetic properties of diluted magnetic semiconductors (DMS) is presented that is based on the local spin-density approximation (LSDA) as implemented in the framework of the tight-binding linear muffin-tin orbital method, while the effect of randomness is described by the coherent potential approximation. Application of a real-space Greenfunction formalism yields ...

first principle calculations were performed using density functional theory within the local spin density approximation (lsda) to understand the electronic properties of au(100)+tbt system and compare the results with au(100) and bulk au properties. band structure, the total dos and charge density for these materials are calculated. we found that the homo for au(100)+tbt becomes broader than au...

In this paper, we propose an Efficient Two-Level I/O Caching Architecture (ETICA) for virtualized platforms that can significantly improve latency, endurance, and cost (in terms of cache size) while preserving the reliability write-pending data blocks. As opposed to previous one-level caching schemes in platforms, our proposed architecture 1) provides two levels by employing both Dynamic Random...

We describe an ab initio theory of finite temperature magnetism in strongly-correlated electron systems. The formalism is based on spin density functional theory, with a self-interaction corrected local spin density approximation (SIC-LSDA). The self-interaction correction is implemented locally, within the KKR multiplescattering method. Thermally induced magnetic fluctuations are treated using...

Traditional Deep Neural Network (DNN) security is mostly related to the well-known adversarial input example attack. Recently, another dimension of attack, namely, attack on DNN weight parameters, has been shown be very powerful. As a representative one, Bit-Flip-based Attack (BFA) injects an extremely small amount faults into parameters hijack executing function. Prior works BFA focus <italic ...

In recent years, memristive crossbar-based neuromorphic computing systems (NCS) have obtained extremely high performance in neural network acceleration. However, adversarial attacks and conductance variations of memristors bring reliability challenges to NCS design. First, can fool the pose a serious threat security critical applications. On other hand, device lead degradation accuracy. this pa...

PARyOpt 1 is a Python based implementation of the Bayesian optimization routine designed for remote and asynchronous function evaluations. especially attractive computational due to its low cost footprint as well ability account uncertainties in data. A key challenge efficiently deploy any strategy on distributed computing systems synchronization step, where data from multiple calls assimilated...

s — and where available for downloading articles — were read and rejected, or included according to the above criteria. Articles were ordered where appropriate. Bibliographies were investigated for possible further research for inclusion. Websites of organisations and departments having conducted research in the field were searched. These included: EPIC, Brandon-Hall, the Masie Centre, elearnin...