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We consider a single-machine scheduling problem with periodic maintenance activities. Although the scheduling problem with maintenance has attracted researchers’ attention, most of past studies considered only one maintenance period. In this research several maintenance periods are considered where each maintenance activity is scheduled after a periodic(More)
To alleviate the computational intensity of Intra encoding for High Efficiency Video Coding (HEVC), we introduce the convolution neural network to reduce the number of the promising CU/PU candidate modes to carry out the exhaustive RDO processing. The practical merits include: Firstly, the proposed algorithm reduces the maximum computational complexity at(More)
The intensive computation of High Efficiency Video Coding (HEVC) engenders challenges for the hardwired encoder in terms of the hardware overhead and the power dissipation. On the other hand, the constrains in hardwired encoder design seriously degrade the efficiency of software oriented fast coding unit (CU) partition mode decision algorithms. A fast(More)
Filtering is one of the core post-processing steps for airborne LiDAR point cloud. In recent years, the morphology-based filtering algorithms have proven to be a powerful and efficient tool for filtering airborne LiDAR point cloud. However, most traditional morphology-based algorithms have difficulties in preserving abrupt terrain features, especially when(More)
This paper investigates single-machine scheduling problems with piece-rate machine maintenance and interval constrained actual processing time. The actual processing time of a job is a general function of the normal job processing time and the position in job sequence, and it is required to restrict in given interval otherwise earliness or tardiness penalty(More)
HEVC doubles the coding efficiency with more than 4x coding complexity as compared to H.264/AVC. To alleviate the burden of Intra encoder, we estimate the RD-cost from the source image textures, and dynamically select two promising CU/PU mode candidates to execute exhaustive RDO processing. As integrated in our hardwired encoder, the averaged 61.7%(More)
In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions(More)
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