Atrous Convolutions and Residual GRU Based Architecture for Matching Power Demand with Supply.

Nowadays, for efficient energy management, local demand-supply matching in power grid is emerging research domain. However, energy demand is increasing day by day in many countries due to rapid growth of the population and most of their work being reliant on electronic devices. This problem has highlighted the significance of effectively matching power demand with supply for optimal energy management.

Text Mining Approaches for Postmarket Food Safety Surveillance Using Online Media.

Food contamination and food poisoning pose enormous risks to consumers across the world. As discussions of consumer experiences have spread through online media, we propose the use of text mining to rapidly screen online media for mentions of food safety hazards. We compile a large data set of labeled consumer posts spanning two major websites.

Towards Efficient Building Designing: Heating and Cooling Load Prediction via Multi-Output Model.

In the current technological era, energy-efficient buildings have a significant research body due to increasing concerns about energy consumption and its environmental impact. Designing an appropriate energy-efficient building depends on its layout, such as relative compactness, overall area, height, orientation, and distribution of the glazing area. These factors directly influence the cooling load (CL) and heating load (HL) of residential buildings.

A review on the state-of-the-art privacy-preserving approaches in the e-health clouds.

Cloud computing is emerging as a new computing paradigm in the healthcare sector besides other business domains. Large numbers of health organizations have started shifting the electronic health information to the cloud environment. Introducing the cloud services in the health sector not only facilitates the exchange of electronic medical records among the hospitals and clinics, but also enables the cloud to act as a medical record storage center.

A comparative analysis of parallel computing approaches for genome assembly.

Over the last two decades, we have witnessed a tremendous growth of sequenced genomic data. However, the algorithms and computational power required to expeditiously process, classify, and analyze genomic data has lagged considerably. In bioinformatics, one of the most challenging and computationally intensive processes, which may take up to weeks of compute time, is the assembly of large size genomes.