Block Mapping Research Articles

GPU-Accelerated Hybrid Discontinuous Galerkin Time Domain Algorithm With Universal Matrices and Local Time Stepping Method

In this article, a graphic processing unit (GPU)-based acceleration implementation of a hybrid discontinuous Galerkin time domain method based on Maxwell’s equations and Helmholtz vector wave equation (HDGTD) has been developed. The computational domain is discretized by tetrahedrons and the resultant meshes are categorized into two regions solved by Maxwell’s equations and Helmholtz vector wave equation, respectively. The hierarchical vector basis functions are used to expand the unknowns in the HDGTD method, and a universal matrix technique is proposed to decompose the geometry-dependent matrices in each tetrahedron into the summation of universal matrices defined in barycentric coordinates, thus giving rise to a great decrease of the memory usage. A local time stepping (LTS) method based on a simple interpolation is introduced in the proposed HDGTD method to achieve highly efficient solution of multiscale problems. Two kinds of compute unified device architecture (CUDA)-based mapping techniques, i.e., 1-D and 2-D blocks, are implemented to achieve a tradeoff between the parallel speedup and the memory usage. With the 1-D block mapping, over 590 times speedup can be achieved, and in the case of the 2-D block mapping, over 150 times acceleration and 13 times memory reduction are obtained. Some practical complex examples are given to demonstrate a good performance of the proposed parallel method.

Morphological comparison of blocks in chaos terrains on Pluto, Europa, and Mars

Chaotic terrains are characterized by disruption of preexisting surfaces into irregularly arranged mountain blocks with a “chaotic” appearance. Several models for chaos formation have been proposed, but the formation and evolution of this enigmatic terrain type has not yet been fully constrained. We provide extensive mapping of the individual blocks that make up different chaos landscapes, and present a morphological comparison of chaotic terrains found on Pluto, Jupiter's Moon Europa, and Mars, using measurements of diameter, height, and axial ratio of chaotic mountain blocks. Additionally, we compare mountain blocks in chaotic terrain and fretted terrain on Mars. We find a positive linear relationship between the size and height of chaos blocks on Pluto and Mars, whereas blocks on Europa exhibit a flat trend as block height does not generally increase with increasing block size. Block heights on Pluto are used to estimate the block root depths if they were floating icebergs. Block heights on Europa are used to infer the total thickness of the icy layer from which the blocks formed. Finally, block heights on Mars are compared to potential layer thicknesses of near-surface material. We propose that the heights of chaotic mountain blocks on Pluto, Europa, and Mars can be used to infer information about crustal lithology and surface layer thickness.

Multi-channel electromyography-based mapping of spontaneous smiles

Objective. Human facial muscle activation underlies highly sophisticated signaling mechanisms that are critically important for healthy physiological function. Accordingly, the necessity to analyze facial muscle activation at high-resolution and in a non-invasive manner is important for the diagnosis and treatment of many medical conditions. However, current clinical examination methods are neither precise nor quantitative. Approach. Wearable, multi-channel surface electromyography can provide a solution to this yet unmet challenge. Here, we present the design and testing of a customized surface electromyography electrode array for facial muscle mapping. Main results. Muscle activation maps were derived from repeated voluntary facial muscle activations. A customized independent component analysis algorithm and a clustering algorithm were developed to identify consistent building block activation patterns within and between participants. Finally, focusing on spontaneous smile analysis and relying on the building block mapping, we classified muscle activation sources, revealing a consistent intra-subject activation and an inter-subject variability. Significance. The herein described approach can be readily used for automated and objective mapping of facial expressions in general and in the assessment of normal and abnormal smiling in particular.

A self-recovery watermarking scheme based on block truncation coding and quantum chaos map

To take into account the invisibility, recovery quality, detection ability, and security, a new digital image fragile watermarking method based on block truncation coding (BTC) and quantum chaos map is proposed. In this method generates the authentication watermark for each 4 × 4 block and generates the recovery watermark for each 2 × 2 block by block truncation coding. For each block, the block truncation coding is used to classify the image blocks into smooth blocks and rough blocks. For different blocks, recovery data can be generated by allocating fewer bits to the smooth blocks and more bits to the rough blocks to encoding the block content. Quantum chaos map is used to generate the block mapping sequence for embedding recovery watermark to improve the shortcoming of watermarking such as small keyspace and low security. The experimental results show that the proposed scheme improves the quality of watermarked and recovered images. Additionally, this approach achieves higher security than the existing methods, under different attacks, such as general tampering, collage attack, content-only, and a hybrid attack.

Structure of block quantum dynamical semigroups and their product systems

Paschke’s version of Stinespring’s theorem associates a Hilbert [Formula: see text]-module along with a generating vector to every completely positive map. Building on this, to every quantum dynamical semigroup (QDS) on a [Formula: see text]-algebra [Formula: see text] one may associate an inclusion system [Formula: see text] of Hilbert [Formula: see text]-[Formula: see text]-modules with a generating unit [Formula: see text]. Suppose [Formula: see text] is a von Neumann algebra, consider [Formula: see text], the von Neumann algebra of [Formula: see text] matrices with entries from [Formula: see text]. Suppose [Formula: see text] with [Formula: see text] is a QDS on [Formula: see text] which acts block-wise and let [Formula: see text] be the inclusion system associated to the diagonal QDS [Formula: see text] with the generating unit [Formula: see text] It is shown that there is a contractive (bilinear) morphism [Formula: see text] from [Formula: see text] to [Formula: see text] such that [Formula: see text] for all [Formula: see text] We also prove that any contractive morphism between inclusion systems of von Neumann [Formula: see text]-[Formula: see text]-modules can be lifted as a morphism between the product systems generated by them. We observe that the [Formula: see text]-dilation of a block quantum Markov semigroup (QMS) on a unital [Formula: see text]-algebra is again a semigroup of block maps.

Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska

Ejection of ballistic blocks was a characteristic feature of the 2016–2017 Bogoslof eruption. High-resolution satellite images acquired throughout the duration of the 9-month long eruptive period permitted the recognition and mapping of ballistic blocks on the surface of Bogoslof Island. Many of the satellite images recorded the accumulation of ballistic material over several individual eruptive events, but a few images recorded the effects of a single event. The nonuniform spatial distribution of blocks suggests that some of the eruption columns were inclined. Ballistic trajectories were estimated using the Eject! model and indicate that accumulation of blocks on Bogoslof Island required launch angles of 45–80° and initial velocities of 50–100 ms−1 to reproduce observed travel distances. The amount of ballistic fallout observed in satellite data indicates that there must have been a shallow submarine source of rock within the conduit/upper edifice system. Dense, accidental cryptodome trachyandesite, and juvenile basalt to trachybasalt scoria make up the bulk of the surface ejecta. Abundant accidental fragments and inclined eruption columns point to periodic vent-wall collapse and jetting around edges of temporarily blocked vents as the likely cause of ballistic ejection.

Linear Maps that Preserve Any Two Term Ranks on Matrix Spaces over Anti-Negative Semirings

There are many characterizations of linear operators from various matrix spaces into themselves which preserve term rank. In this research, we characterize the linear maps which preserve any two term ranks between different matrix spaces over anti-negative semirings, which extends the previous results on characterizations of linear operators from some matrix spaces into themselves. That is, a linear map T from p × q matrix spaces into m × n matrix spaces preserves any two term ranks if and only if T preserves all term ranks if and only if T is a ( P , Q , B )-block map.

An Efficient Deep Unsupervised Superresolution Model for Remote Sensing Images

Superresolution (SR) has provided an effective solution to the increasing need for high-resolution images in remote sensing applications. Among various SR methods, deep learning-based SR (DLSR) has made a significant breakthrough. However, supervised DLSR methods require a considerable amount of training data, which is hardly available in the remote sensing field. To address this issue, some research works have recently proposed and revealed the capability of deep learning in unsupervised SR. This article presents an efficient unsupervised SR (EUSR) deep learning model using dense skip connections, which boosts the reconstruction performance in parallel with the reduction of computational burden. To do this, several blocks containing densely connected convolutional layers are implemented to increase the depth of the model. Some skip connections also concatenate feature maps of different blocks to enable better SR performance. Moreover, a bottle-neck block abstracts the feature maps in fewer feature maps to remarkably reduce the computational burden. According to our experiments, the proposed EUSR leads to better results than the state-of-the-art DLSR method in terms of reconstruction quality with less computational burden. Furthermore, results indicate that the EUSR is more robust than its rival in dealing with images of different classes and larger sizes.

Single Low-Dose CT Image Denoising Using a Generative Adversarial Network With Modified U-Net Generator and Multi-Level Discriminator

Low-dose CT (LDCT) images have been widely applied in the medical imaging field due to the potential risk of exposing patients to X-ray radiations. Given the fact that reducing the radiation dose may result in increased noise and artifacts, methods that can eliminate the noise and artifacts in the LDCT image have drawn increasing attentions and produced impressive results over the past decades. However, recent proposed methods mostly suffer from noise remaining, over-smoothing structures or false lesions derived from noise. In this paper, we propose a generative adversarial network (GAN) with novel architecture and loss function for restoring the LDCT image. Firstly, the inception-residual block and residual mapping are incorporated in the U-Net structure. The modified U-Net is applied as the generator of the GAN network so that the noise feature can be eliminated during the forward propagation. Secondly, a novel multi-level joint discriminator is designed by concatenating multiple convolutional neural networks (CNNs) where the output of each deconvolutional layer in the generator is compared with the corresponding down-sampled ground truth image. The adversarial training can be sensitive to noise and artifacts in different scales with this discriminator. Thirdly, we novely define a loss function consisting of the least square adversarial loss, VGG based perceptual loss, MSE based pixel loss and the noise loss, so that the differences in pixel, visual perception and noise distribution are comprehensively considered to optimize the network. Experimental results on both simulated and official simulated clinical images have demonstrated that the proposed method can provide superior performance to the state-of-the-art methods in noise removal, structure preservation and false lesions elimination.

HUBUNGAN KARAKTERISTIK LAHAN DENGAN PRODUKTIVITAS TBS (Studi Kasus pada PT. Perkebunan Nusantara VIII Cimulang, Bogor)

Oil palm (Elaeis guineensis Jacq) is an important crop for Indonesia as one of non fuel export commodities. Development, improvement of quality and productivity of oil palm is influenced by a lot of factors, among others are land characteristics. This research was aimed to know the relationship between oil palm productivity and physical land characteristic including soil, slope and the crop age. The results of this research were expected to be useful to improve oil palm productivity and the oil palm plantation development.This research was done within the site of PT. Perkebunan Nusantara VIII at Cimulang, Bogor. In this research, analyzing correlation between productivity of blocks that have homogenous land characteristic with physical land characteristic parameter including soil and slope. Block with homogenous land characteristic was block which 75% or more of it’s area had similar characteristics. These blocks were determined by overlying block map, slope map and soil map. The result show that were 20 homogenous blocks out of all the 38 blocks of the site the PT. Perkebunan Nusantara VIII at Cimulang. Average production was depend on crop age. At study areas, the highest average fresh fruit bunch production obtained from plants 5 years, which was equal to 22.87 tons acre-1 year-1 and the lowest average fresh fruit bunch production obtained from plants 3 years, which was equal to 0.66 tons acre-1 year-1. Based on soil, the highest average fresh fruit bunch production obtained from the SPT 11 (Typic Eutrudox), which was equal to 12.54 tons/acre/year and the lowest average fresh fruit bunch production obtained from SPT 1 (Oxic Dystropept), which was equal to 9.51 tons/acre/year. Based on slope class, the highest average fresh fruit bunch production obtained from block with slope class B (8-15%), which was equal to 12.54 tons/acre/year, and the lowest average production was equal to 9.98 tons/acre/year from the slope class.

Block maps and Fourier analysis

We introduce block maps for subfactors and study their dynamic systems. We prove that the limit points of the dynamic system are positive multiples of biprojections and zero. For the ℤ2 case, the asymptotic phenomenon of the block map coincides with that of the 2D Ising model. The study of block maps requires a further development of our recent work on the Fourier analysis of subfactors. We generalize the notion of sum set estimates in additive combinatorics for subfactors and prove the exact inverse sum set theorem. Using this new method, we characterize the extremal pairs of Young’s inequality for subfactors, as well as the extremal operators of the Hausdorff-Young inequality.

Multistep block mapping on principal component uniformity repairs Landsat 7 defects

Landsat 7 Scan Line Corrector failure compromised 22% of pixels. Novel procedures were developed estimating missing data from means of pixels present within 2N–sized neighbouring blocks whose positions were defined by simultaneously minimizing heterogeneity of source imagery within blocks while satisfying need for sufficiently large size that some pixels remained near defects. Regions used to estimate missing data were defined in a stepwise process in which local standard error cut-offs for accepting particular 2N–sized regions of source imagery as representing missing pixels were progressively raised over a series of 51 cycles. For Landsat scenes of interest in western Oregon, averages of 34.7, 68.8, 95.4, and 99.0% of gaps in synthetic data were repaired by cycles 1, 6, 16, and 30. Standard deviations of differences between estimated and real values increased from an average of 9.0 digital numbers at cycle 1 to plateaus near 17.0 by cycle 25. This procedure performed well over a wide range of imagery dates, a consequence of its use of source imagery to identify homologous regions within landscapes rather than directly estimating pixels.

Protocol Function Block Mapping of Software Defined Protocol for 5G Mobile Networks

In this paper, we propose software-defined protocol (SDP) technique to facilitate flexible service-oriented protocol stack deployment for providing high-throughput, low-latency and elastic mobile services based on platform virtualization and functionality modularization. We first elaborate the principle of SDP and then address one of the most important issues in SDP, namely SDP request mapping (SDPM), where an SDP request is fulfilled by mapping a set of required SDP function blocks and virtual links onto underlying SDP servers. We formulate the SDPM problem as a mixed integer programming (MIP). To address the $\mathcal {N}\mathcal {P}$ -hardness and scalability of SDPM problem, we propose a decomposition algorithm which breaks down the SDPM problem into inter-block link and block mapping problems to accomplish the upper bound (UB) and lower bound (LB) of the MIP solution, respectively. The optimality can be achieved when the UB and the LB converges by using iterations. We employ LTE Layer-2 data-plane processing as a benchmark for validating the effectiveness of the SDP technique and evaluate the performance of SDPM algorithm. Numerical results show that SDP is effective to provide elastic low-latency mobile services and the proposed SDPM algorithm significantly outperforms the benchmark in stack processing delay, mapping cost, and resource utilization.

Extracting spatial patterns of urban gas pipeline risk considering social and structural parameters of urban blocks

Due to growing cities and urbanization, the demand for natural gas is increasing rapidly around the world. To address this necessity, the density of urban natural gas pipelines will increase. However, urban pipelines pass through regions with the high density of people and buildings with low construction quality, possibly leading to accidents that may cause extreme damage to people and property. In this paper, a quantitative method is proposed for evaluation of hazards that are influenced by the inherent parameters of gas pipelines considering their density. Afterwards, considering the physical and social vulnerabilities of this study area, the structural and social parameters of urban blocks are added to the risk model. The output of this method is used to analyze the risk of spatial patterns of urban natural gas pipelines and the structural and social parameters of urban blocks. This research model consists of the following three main sections: hazard mapping of urban gas pipelines considering their inherent parameters, physical and social vulnerability mapping of urban blocks, and risk mapping of gas pipelines. The results show that there are meaningful spatial patterns in risk distributions that can be analyzed by the vulnerability results. The output of the proposed method has many applications in the fields of disaster management, urban planning and incident prediction.

Using multi-level fusion of local features for land-use scene classification with high spatial resolution images in urban coastal zones

Monitoring scene-level land-use in urban coastal zones has become a critical and challenging task, due to the rising risk of marine disasters and the greater number of scene classes such as harbors. Since street blocks are physical containers of different classes of land-use in urban zones, some scene classification methods based on high-spatial-resolution remote sensing images take blocks segmented by roads as classification units. However, these methods extract handcrafted low-level features from remote sensing images, limiting their ability to represent street blocks. To extract semantically meaningful representations of street blocks, the sparse auto-encoder (SAE) model was employed for local feature extraction in this paper and a multi-level method based on the fusion of local features was proposed for block-based land-use scene classification in urban coastal zones. First, convolved feature maps of street blocks were extracted by taking the hidden layer of the SAE as convolution kernels. Then, the local features were fused at three levels to generate more robust and discriminative representations of patches in convolved feature maps. The combination patterns and the absolute relationship of local features were captured at the first and second level, respectively. A convolution neural network was utilized to make the local features more discriminative to semantic information at the third level. Finally, the bag-of-visual-words model was employed to generate global features for street blocks. The proposed method was tested for Qingdao, China using Gaofen-2 (GF-2) satellite images and an overall accuracy of 83.80% was achieved in the study area. The classification results indicate that the proposed method in concert with GF-2 images has potential for accurately monitoring land-use scenes in urban coastal zones.

Scale-Free Sparse Matrix-Vector Multiplication on Many-Core Architectures

Sparse matrix-vector multiplication (SpMV) is one of the most important kernels for many applications. In this paper, we study the implementation of SpMV for scale-free matrices on many-core architectures including graphic processing units and Xeon Phi coprocessors. We first propose a hardware oblivious implementation for heterogeneous many-core processors using OpenCL. Our OpenCL implementation uses a novel SpMV format called hybrid COO+CSR (HCC), which employs 2-D jagged partitioning to balance the workload among a large number of cores and improve the data locality. Moreover, the OpenCL implementation is designed to be parametric, which allows systematic performance tuning. We conduct experiments to evaluate the efficiency of our hardware oblivious implementation. Experiments show that it achieves comparable performance to the Intel MKL and state-of-the-art OpenCL-based ViennaCL library implementation. Although the OpenCL implementation provides functional portability for heterogeneous systems, it fails to take advantage of the low-level architectural features. To further improve the performance, we propose a hardware conscious implementation using the native parallel programming language. We use the Xeon Phi platform as a case study. In our hardware conscious implementation, we ensure that the HCC format efficiently utilizes the vector process units on Xeon Phi by employing low-level intrinsics, and improve the overall performance through locality-aware block mapping, and intrablock tiling. Experiments using a wide range of representative scale-free matrices demonstrate that compared with the OpenCL-based hardware oblivious implementation, the hardware conscious implementation achieves $2.2\boldsymbol {\times }$ speedup on average. Compared with MKL, the hardware conscious implementation achieves $3.1\boldsymbol {\times }$ speedup on Xeon Phi.

Low-Latency High-Efficiency Mobile Fronthaul With TDM-PON (Mobile-PON)

To meet the capacity requirements of the exponential increase in mobile traffic and to continue to drive down the per-bit cost for mobile service providers, the cloud radio access network (C-RAN) has become a crucial step toward 5G. However, the current C-RAN architecture has some major drawbacks in terms of scalability, cost, and efficiency. In this paper, we propose and numerically demonstrate a novel mobile fronthaul architecture based on functional split and time-division multiplexed (TDM) passive optical networks (PONs) with a unified mobile and PON scheduler known as Mobile-PON. The optimal functional split distributes lower physical layer hardware toward remote radio sites. The new interface that divides the remote radio processing, and centralized baseband processing requires less bandwidth, also opens the possibility of sharing and multiplexing the bandwidth with multiple remote sites. Our combined mobile and PON scheduler is mainly based on the more complex wireless scheduling that translates its results into the TDM-PON system through LTE resource block mapping, eliminating additional scheduling delay at the PON. Without the additional scheduling delay, the cost-effective TDM-PON becomes applicable for mobile fronthaul, while the optimal fronthaul interface increases bandwidth efficiency by ∼10× over CPRI.

Estimation of accuracy in determining the translational velocity of a video camera using data from optical flow

The devised approaches are adapted to the complicated conditions of observation in certain real tasks, and are fully operational in those cases when existing standard algorithms fail to give reliable results. We propose a method for determining dynamic motion parameters based on the algorithm of a dense optical flow using a texture analysis. In order to determine an optical flow, we employed a block mapping method that uses adaptively variable size and adaptive motion vector search strategy with weighting the measurements of image blocks, where each block is matched with a texture indicator. A standard block method for estimating optical flow does not imply the use of weighting of the image blocks. A measure of the image block texturization and, consequently, the reliability of the computed motion vector, is determined on the basis of conditionality number of the information matrix. Based on the calculated optical flow, in order to estimate motion parameters, it is proposed to use the least square method that takes into account noise of the measured data. In this case, the minimization is applied at which a contribution to an error is weighed, greater importance is given to the points where the optical flow speed is larger. This is most useful when the measurement of high speeds is more accurate. The norm that produces the best results depends on the noise properties in the measured optical flow. When estimating parameters of the translational motion velocity of the entire image frame, the proposed method considers textural differences of the underlying surface, as well as noise in the measured data of each image block.We presented simulation results of a UAV motion along different types of the underlying surface and estimated the accuracy of determining translational motion parameters using the optical sensor. Experimental results confirm that the application of a texture analysis when evaluating a motion field improves performance by recruiting a reduced number of vectors, as well as this proves to be more accurate in comparison with traditional block brute-force methods

Population structure, genetic relatedness and linkage disequilibrium blocks in cultivars of tropical soybean (Glycine max)

Soybean (Glycine max L.) is an annual, self-pollinated species, whose genetic base in Brazil is the result of several cycles of selection and effective recombination among a relatively small number of genotypes selected from the USA cultivars. This frequent selection, admixed population, and the crossing of a small number of cultivars can lead to increase the genetic relationship and affect the patterns of population structure. These factors affect the patterns of linkage disequilibrium (LD) blocks, which can be an effective approach for the screening of target loci for agricultural traits in cultivars of tropical soybean. The objectives of this research were to analyze LD blocks, estimate population structure and relatedness through of genotyping of 169 cultivars of tropical soybean by using a BARCSoySNP6K of Illumina iScan platform. The genotyping revealed a high genetic relatedness and population structure among the cultivars of soybean in Brazil, suggesting the existence of a shared genetic base. Our results provide a help to understand the distribution of genetic variation contained within the Brazilian soybean cultivar collection. We showed that the extensive use of a small number of elite genotypes in Brazilian breeding program further reduced the genetic variability, generate extensive LD and probably increase the haplotype block size. These results are in agreement with results of USDA soybean collection, mainly with accessions of north American, when compared with wild and landraces accessions. We constructed a small haplotype block maps (941 blocks), which may be useful for association studies aimed at the identification of genes controlling traits of economic importance in soybean.

I/O access frequency-aware cache method on KVM/QEMU

Together with the rapid development of IT technology, cloud computing has been considered as the next generation's computing infrastructure. One of the essential part of cloud computing is the virtual machine technology that enables to reduce the data center cost with better resource utilization. Especially, virtual desktop infrastructure (VDI) is receiving explosive attentions from IT markets because of its advantages of easier software management, greater data protection, and lower cost. However, sharing physical resources in VDI to consolidate multiple guest virtual machines (VMs) on a host has a tradeoff that can lead to significant I/O degradation. Optimizing I/O virtualization overhead is a challenging task because it needs to scrutinize multiple software layers between guest VMs and host where those VMs are executing. In this paper, we present a hypervisor-level cache, called hyperCache, which is possible to provide a shortcut in KVM/QEMU. It intercepts I/O requests in the hypervisor and analyses their I/O access patterns to select data retaining high access frequency. Also, it has a capability of maintaining the appropriate cache memory size by utilizing the cache block map. Our experimental results demonstrate that our method improves I/O bandwidth by up to 4.7x over the existing QEMU.