Abstract In this paper, we present a new method for digital image compression. This method involves dividing the wavelet spectrum into several sub-bands after a certain level of regular or irregular decay. Each sub-band is then decomposed using an inverse pyramid algorithm and a linear orthogonal transform like DCT. Depending on whether you want lossless compression or lossy compression, all or... In this paper, we present a new method for digital image compression. This method involves dividing the wavelet spectrum into several sub-bands after a certain level of regular or irregular decay. Each sub-band is then decomposed using an inverse pyramid algorithm and a linear orthogonal transform like DCT. Depending on whether you want lossless compression or lossy compression, all or only some spectral coefficients of the inverse pyramid are retained. Entropy coding is then applied. Higher compression ratios are achieved at higher image quality levels than some popular algorithms from the practice. Read More Read Less

Abstract In this paper, we look at power consumption for fault-tolerant real-time systems. Specifically, we look at real-time systems where fault tolerance is reached by repeatedly running a task affected by the transient fault with time redundancy. We conduct a power consumption analysis for real-time fault tolerant systems using a heuristic-based dynamic voltage and frequency scaling algorithm that we developed. Simulation... In this paper, we look at power consumption for fault-tolerant real-time systems. Specifically, we look at real-time systems where fault tolerance is reached by repeatedly running a task affected by the transient fault with time redundancy. We conduct a power consumption analysis for real-time fault tolerant systems using a heuristic-based dynamic voltage and frequency scaling algorithm that we developed. Simulation results demonstrate that our algorithm can be used successfully for power consumption based on fault tolerance analysis. Read More Read Less

Abstract In this paper, we demonstrated an effective way to visualize 2D weather products using a Marching Squares approach. We explore the possibility of extracting both isoline and color-filled iso-areas and improvements to avoid the standard broken polyline Marching Squares result and force smoother visualization. We test and validate this approach using different sampling resolutions and parameters on the real weather... In this paper, we demonstrated an effective way to visualize 2D weather products using a Marching Squares approach. We explore the possibility of extracting both isoline and color-filled iso-areas and improvements to avoid the standard broken polyline Marching Squares result and force smoother visualization. We test and validate this approach using different sampling resolutions and parameters on the real weather temperature products. Read More Read Less