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In high-performance computing (HPC) platform, resource usage pattern changes over time which makes the resource monitoring a challenge. Maintaining the performance goals within a good power range is very critical where servers suffer from under utilisation, failure or degraded hardware support. Better forecast of the workload can reduce the energy cost by predicting the future workload more accurately...
To ensure reliable communication and improve performance of a wireless communication system, it is required for the transmitter and receiver to have fair knowledge about the channel state information (CSI). Analysis of the basic channel prediction schemes like Parametric Radio channel model, Autoregressive model based prediction and Bandlimited basis expansion is done in this paper. Subspace based...
In this paper a lossless compression scheme is presented. In this scheme we have compared our newly proposed model with lossless predictive code (LPC) and differential pulse code modulation (DPCM) and we have shown how our model is more advantageous than LPC and DPCM. This newly proposed scheme for Huffman coding will achieve higher compression as we have reduced the mean value of the pixel in the...
Recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. Concomitantly, there is an increased trend towards the forecasting of system degradation through a prognostic process to fulfill the needs of customers demanding high vehicle...
Data mining deals with extracting or mining knowledge from large and infinite amount of stream data. It also handles the data quality with limited volume of disk or memory. In such traditional transaction environment it is impossible to perform frequent items mining because it requires analyzing which item is a frequent one to continuously incoming stream data and which is probable to become a frequent...
The value of models as tools to design and plan networks, aid the decision-making process, and as methods to conceptualize abstract ideas is well known. Models play a key role in evaluating varied design options and assist in discovering design issues that likely will impact performance. In the service delivery platform, spreadsheet models can be applied to learn about strategic traffic volume, estimate...
The prediction of biological activity of a chemical compound from its structural features, representing its physico-chemical properties, plays an important role in drug discovery, design and development. Since the biological data is highly non-linear, the machine-learning techniques have been widely used for modeling it. In the present work, the clustering, genetic algorithm (GA) and artificial neural...
The Land Information System (LIS) is a multiscale hydrologic modeling and data assimilation framework that integrates the use of satellite and ground-based observational data products with advanced land-surface modeling tools to aid several application areas, including water resources management, numerical weather prediction, agricultural management, air quality, and military mobility assessment.
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