Constrained dynamic performance and control models of complex engineering systems can be represented in the form of a Differential Algebraic Equation (DAE) system. The high-index of this DAE system poses computational ...

Artificial Neural Networks (ANNs) are algorithmic techniques that simulate biological neural systems. Typical realization of ANNs are software solutions using High Level Languages (HLLs) such as C, C++, etc. Such solutions ...

With modern computational tools, modeling light scattering from a particle with known physical parameters has become relatively trivial. Evaluation using analytical solutions is highly eficient compared to a full ...

Phase Change Memory (PCM) is a recently developed non-volatile memory technology that is expected to provide an attractive combination of the best features of conventional disks (persistence, capacity) and of DRAM (access ...

Nowadays, we have millions of cameras in public places such as traffic junctions, railway stations etc., and capturing video data round the clock. This humongous data has resulted in an increased need for automation of ...

Enterprise Database Management Systems (DBMSs) have to contend with resource-intensive and time-varying workloads, making them well-suited candidates for migration to cloud plat-forms { specifically, they can dynamically ...

Computational imaging has been playing an important role in understanding and analysing the captured images. Both image segmentation and restoration has been in-tegral parts of computational imaging. The studies performed ...

Deep neural networks with millions of parameters are at the heart of many state of the art computer vision models. However, recent works have shown that models with much smaller number of parameters can often perform just ...