Uniform Partitioning Research Articles

Tile Adaptation for Workload Balancing of 3D-HEVC Encoder in Homogeneous Multicore Systems

This paper proposes a tile adaptation for workload balancing to speed up the 3D-High Efficiency Video Coding (3D-HEVC) encoder. Experiments were done to evaluate the usage of tiles when encoding texture and depth maps considering a static uniform partitioning. Based on these evaluations, we observed that the encoding workload of neighboring frames in the same view tends to be similar. Moreover, the encoding workload of dependent views can be predicted using the information of previously encoded frames of the same and base views. Therefore, the proposed solution adaptively defines the boundaries of the tiles based on inter-frame and inter-view correlations to balance the workloads of the tiles, resulting in a higher speedup when executing in homogeneous multicore systems. The proposed method was implemented in 3D-HEVC Test Model and evaluated according to the Common Test Conditions. The results demonstrated that the proposed solution speeds up texture and depth map coding from 9.94% to 18.21%, when compared to the uniform-sized tiles, without coding efficiency loss. To the best of the authors' knowledge, this is the first work proposing a complete solution for speeding up the 3D-HEVC video encoder by balancing the tiles workload dynamically.

A numerical method for simulating planar 3D multi-fracture propagation in multi-stage fracturing of horizontal wells

To resolve the issue of design for multi-stage and multi-cluster fracturing in multi-zone reservoirs, a new efficient algorithm for the planar 3D multi-fracture propagation model was proposed. The model considers fluid flow in the wellbore-perforation-fracture system and fluid leak-off into the rock matrix, and uses a 3D boundary integral equation to describe the solid deformation. The solid-fluid coupling equation is solved by an explicit integration algorithm, and the fracture front is determined by the uniform tip asymptotic solutions and shortest path algorithm. The accuracy of the algorithm is verified by the analytical solution of radial fracture, results of the implicit level set algorithm, and results of organic glass fracturing experiment. Compared with the implicit level set algorithm (ILSA), the new algorithm is much higher in computation speed. The numerical case study is conducted based on a horizontal well in shale gas formation of Zhejiang oilfield. The impact of stress heterogeneity among multiple clusters and perforation number distribution on multi-fracture growth and fluid distribution among multiple fractures are analyzed by numerical simulation. The results show that reducing perforation number in each cluster can counteract the effect of stress contrast among perforation clusters. Adjusting perforation number in each cluster can promote uniform flux among clusters, and the perforation number difference should better be 1-2 among clusters. Increasing perforation number in the cluster with high in situ stress is conducive to uniform fluid partitioning. However, uniform fluid partitioning is not equivalent to uniform fracture geometry. The fracture geometry is controlled by the stress interference and horizontal principal stress profile jointly.

Iterative Fuzzy Modeling of Hydrogen Fuel Cells by the Extended Kalman Filter

Hydrogen economy is one of the recently opened alternatives in the field of non-polluting energy. Hydrogen fuel cells show high performance, high reliability in stationary applications and minimal environmental impact. To increase the efficiency of the hydrogen fuel cell it is very important to have a good model to predict its dynamic behavior. In addition, this model must be able to adapt iteratively to the changes that occur in its performance due to operating conditions and even to the degradation through its lifespan. This paper presents the application of an iterative fuzzy modeling methodology based on the extended Kalman filter applied to a real hydrogen fuel cell. Two algorithms based on the Kalman filter will be compared with the well-known backpropagation algorithm from three different initializations: by uniform partitioning, subtractive clustering and CMeans clustering. The used data have been collected during the actual operation of a real 3.4 kW proton exchange membrane fuel cell. As the article experimentally shows, the Takagi-Sugeno type fuzzy model allows to create a very accurate nonlinear dynamic model of the fuel cell, which can be very useful to design an efficient fuel cell control system.

GraphA: Efficient Partitioning and Storage for Distributed Graph Computation

Distributed graph computation is central to applications ranging from language processing to social networks. However, natural graphs tend to have skewed power-law distributions where a small subset of the vertices have a large number of neighbors. Existing graph-parallel systems suffer from load imbalance, high communication cost, and inefficient processing. To address this problem, in this paper we present GraphA, an a daptive scheme for efficient large-scale graph computation. At the core of GraphA is an adaptive and uniform graph partitioning algorithm, which partitions the datasets by using an incremental number of mapping functions. GraphA further improves and leverages the ART index structure to realize fine-grained and low-cost graph storage. We have implemented GraphA both on Spark and on GraphLab. Extensive evaluation shows that GraphA significantly outperforms state-of-the-art graph-parallel systems (GraphX and PowerLyra) in ingress time, execution time and storage cost, for both real-world and synthetic graphs. GraphA achieves up to $7.1\times$ 7 . 1 × performance improvement over GraphX and 19.7 percent improvement over PowerLyra.

Microstructural Evolution and Deformation Behavior of Ni-Si- and Co-Si-Containing Metastable High Entropy Alloys

Two high entropy alloy (HEA) compositions were compared to explore the individual effects of Co and Ni on phase stability and resultant deformation response in Fe-Mn-Cr-Si-containing HEAs. It was observed that Co-Si-containing HEA depicted responsive phase evolution upon friction stir processing owing to decreased γ (f.c.c.) matrix stability as against Ni-Si-containing HEA. As a result, the Co-Si HEA showed the presence of dual-phase microstructure with the dominance of e (h.c.p.) phase (52 pct), whereas the Ni-Si HEA showed single-phase γ microstructure under similar processing condition. Also, the dominant deformation mechanisms were different in the two alloys. Co-Si HEA showed uniform strain partitioning between the f.c.c. and h.c.p. phases. Conversely, single-phase f.c.c. microstructure in Ni-Si HEA accommodated strain by twinning-induced plasticity.

A semi-analytical model for predicting fluid partitioning among multiple hydraulic fractures from a horizontal well

Multiple fracture growth during multi-cluster fracturing of a horizontal well is closely dependent on fluid partitioning. However, whether injected fluid can uniformly flux into multiple fractures during fracturing remains uncertain.In this study, a semi-analytical model was proposed to simulate fluid rate distribution in multiple fractures. Multi-fracture interaction stresses in the model are solved by a detailed approximation of the elastic solution for a pressurized fracture, which are integrated with rock deformation equations to calculate the multi-fracture width. The semi-analytical model was validated with a well-recognized fully coupled hydraulic fracture simulator. The semi-analytical model can efficiently optimize perforation parameters for multi-cluster fracturing of a horizontal well.Sensitivity analysis was conducted by using the model, and simulation results show that perforation friction and interaction stress are two key factors that determine fluid partitioning among multiple fractures. When interaction stress dominates the flow pressure drop in multiple fractures, fluid partitioning among multiple fractures is uneven due to heterogeneous interaction stresses among multiple fractures; otherwise, fluid partitioning is evenly distributed. Decreasing the total number or diameter of perforation holes can promote uniform multi-fracture growth and fluid partitioning. Homogenous fluid partitioning can be achieved by decreasing the perforation number of exterior fractures, whereas increasing the perforation number of interior fractures minimally affects uniform fluid partitioning among multiple fractures.

Long-Term Ensemble Learning for Cross-Season Visual Place Classification

This paper addresses the problem of cross-season visual place classification (VPC) from the novel perspective of long-term map learning. Our goal is to enable transfer learning efficiently from one season to the next, at a small constant cost, and without wasting the robot’s available long-term-memory by memorizing very large amounts of training data. To achieve a good tradeoff between generalization and specialization abilities, we employ an ensemble of deep convolutional neural network (DCN) classifiers and consider the task of scheduling (when and which classifiers to retrain), given a previous season’s DCN classifiers as the sole prior knowledge. We present a unified framework for retraining scheduling and we discuss practical implementation strategies. Furthermore, we address the task of partitioning a robot’s workspace into places to define place classes in an unsupervised manner, as opposed to using uniform partitioning, so as to maximize VPC performance. Experiments using the publicly available NCLT dataset revealed that retraining scheduling of a DCN classifier ensemble is crucial in achieving a good balance between generalization and specialization. Additionally, it was found that the performance is significantly improved when using planned scheduling.

Fuzzy logic model for pullout capacity of near-surface-mounted FRP reinforcement bonded to concrete

The application of fiber-reinforced polymer (FRP) strips or rods in the form of near-surface-mounted (NSM) reinforcement has become an attractive solution to strengthen the existing buildings and bridges. It is of interest to engineers to have an accurate estimate of the bond capacity of this technique. In this paper, fuzzy logic approach is utilized to propose an alternative method of determining the pullout strength of NSM FRP strips/rods which are bonded to the concrete block. Two types of fuzzy logic models, namely Mamdani and Takagi–Sugeno, are developed. With the aim of enhancing the interpretability of the fuzzy model, the rule base of Mamdani model is extracted from the classification decision tree, and the membership functions corresponding to the linguistic concepts are built by uniform partitioning the range of variables. On the other hand, in order to arrive at closed-form equations for pullout capacity, the subtractive clustering algorithm is employed to deduce the rule base and membership functions of Takagi–Sugeno model (first order), and its consequent part is tuned by the least square optimization using training dataset. Several fuzzy logic models of both types with different numbers of rules are developed and compared in terms of different error measures. To train and validate the fuzzy models, a large database of 384 direct pullout tests on NSM FRP bonded to concrete is assembled from the literature. The results reveal that both of the proposed Mamdani and Takagi–Sugeno models demonstrate good accuracy against the experimental data and outperform the published models. A parametric study indicates that the proposed fuzzy models can predict the maximum effective bond length, and thus, they are able to capture the underlying mechanics of the problem.

Extremely high strength and work hardening ability in a metastable high entropy alloy

Design of multi-phase high entropy alloys uses metastability of phases to tune the strain accommodation by favoring transformation and/or twinning during deformation. Inspired by this, here we present Si containing dual phase Fe42Mn28Co10Cr15Si5 high entropy alloy (DP-5Si-HEA) exhibiting very high strength (1.15 GPa) and work hardening (WH) ability. The addition of Si in DP-5Si-HEA decreased the stability of f.c.c. (γ) matrix thereby promoting pronounced transformation induced plastic deformation in both as-cast and grain refined DP-5Si-HEAs. Higher yet sustained WH ability in fine grained DP-5Si-HEA is associated with the uniform strain partitioning among the metastable γ phase and resultant h.c.p. (ε) phase thereby resulting in total elongation of 12%. Hence, design of dual phase HEAs for improved strength and work hardenability can be attained by tuning the metastability of γ matrix through proper choice of alloy chemistry from the abundant compositional space of HEAs.

Structural discontinuity as generalized strain and Fourier transform for discrete-continuous systems

We consider a segmented structure, possibly connected with a continuous medium, as initially homogeneous, where discontinuities arise as localized strains induced by self-equilibrated localized actions. Under this formulation augmented by interface conditions, the linearized formulation remains valid. This approach eliminates the need for examining separate sections with subsequent conjugation. Only conditions related to the discontinuities should be satisfied, while the continuity in other respects preserves itself automatically. No obstacle remains for the continuous Fourier transform. For a uniform partitioning, the discrete transform is used together with the continuous one. We demonstrate the technique by obtaining the Floquet wave dispersive relations with their dependence upon interface stiffness. To this end, we briefly consider the flexural wave in the segmented beam on Winkler’s foundation, the gravity wave in a plate (also segmented) on deep water and the Floquet–Rayleigh wave in such a plate on an elastic half-space. Besides, we present the wave equations developed for an elastic medium with discontinuities.

Reversed strength-ductility relationship in microstructurally flexible high entropy alloy

Conventional high strength alloys lack ductility due to lower work hardening and early onset of damage nucleation. To overcome this deficiency, high entropy alloys (HEAs) enjoy the benefit of metastability of phases to tune the deformation mechanisms for engineering strength and ductility. Inspired by this, here we present friction stir processed Fe40Mn20Co20Cr15Si5 HEA with ultrafine face centered cubic (f.c.c.) γ grains embedded in a refined hexagonal closed packed (h.c.p) ε matrix. Transformation of γ grains and twinning in ε matrix triggered uniform strain partitioning among these phases and sustained work hardening during deformation thereby reversing the conventional strength-ductility trade-off.

Normalized Scalar Product Approach for Nearshore Bathymetric Estimation From X-Band Radar Images: An Assessment Based on Simulated and Measured Data

This paper investigates the capability of X -band radar systems to estimate nearshore bathymetry fields by considering both simulated and measured radar data. For the first time, a sensitivity analysis is performed to evaluate how sea-state conditions affect bathymetric estimates. For this purpose, sea wave fields generated by means of a numerical model, based on a nonlinear shallow-water equation solver, are used. Starting from the synthetic radar data, which represent the input of the bathymetric estimation algorithm, the bathymetric reconstruction is performed through the normalized scalar product (NSP) estimation strategy, exploiting a spatial partitioning of the radar data. In this way, it is possible to improve the accuracy of the estimates in nearshore areas, where the space-varying behavior of the sea depth and the presence of coastlines or coastal structures typically leads to a spatial inhomogeneity of the wave motion. In this regard, it is shown how the choice of the partitioning settings affects the bathymetric estimates obtained from high-resolution X -band radar images by using the NSP strategy. In addition, an adaptive partitioning strategy that takes into account the wave evolution in nearshore shallow waters is devised. Based on both simulated and measured radar data, the accuracy of the bathymetric estimates achievable through the proposed adaptive partitioning process and that obtained by exploiting the approach using uniform spatial partitioning are compared. The results obtained confirm the robustness of the NSP technique with respect to sea conditions and, moreover, demonstrate that the proposed adaptive partitioning strategy provides more accurate bathymetric estimates than those obtained with the space-invariant partitioning procedure.

Toward the design of a novel hybrid parallel N-body method in scope of modern cloud architectures

A hybrid parallel self mesh-adaptive N-body method based on approximate inverses and multiprojection techniques is proposed. This method is a three-dimensional hybrid parallel mesh-type N-body scheme based on the solution of the Poisson equation in the physical space with boundary conditions obtained from multipole expansion formulas. In order to improve the accuracy of the solution, especially in shallow regions, a self mesh-adaptive scheme is used to create a hierarchy of independent smaller N-body problems. The parallelization of the scheme is based on a uniform partitioning of the bodies with respect to available computer nodes, and communications are required only for the computation of the density and potential distributions. The proposed scheme is suitable for large-scale galaxy simulations with millions of bodies on high-resolution meshes, for distributed HPC systems with multicore computer nodes. Moreover, large-scale galaxy simulations are performed on modern Cloud environments in order to examine the applicability and performance. Implementation issues concerning the proposed scheme are also discussed. The parallel performance and speedup of the hybrid parallel N-body method on HPC systems as well as on Cloud environments are presented and discussed.

Self-adaptive type-1/type-2 hybrid fuzzy reasoning techniques for two-factored stock index time-series prediction

Considerable research outcomes on stock index time-series prediction using classical (type-1) fuzzy sets are available in the literature. However, type-1 fuzzy sets cannot fully capture the uncertainty involved in prediction because of its limited representation capability. This paper fills the void. Here, we propose four chronologically improved methods of time-series prediction using interval type-2 fuzzy sets. The first method is concerned with prediction of the (main factor) variation time-series using interval type-2 fuzzy reasoning. The second method considers secondary factor variation as an additional condition in the antecedent of the rules used for prediction. Another important aspect of the first and the second methods is non-uniform partitioning of the dynamic range of the time-series using evolutionary algorithm, so as to ensure that each partition includes at least one data point. The third method considers uniform partitioning without imposing any restriction on the number of data points in a partition. The partitions are here modeled by type-1 fuzzy sets, if there exists a single block of contiguous data, and by interval type-2 fuzzy sets, if there exists two or more blocks of contiguous data in a partition. The fourth method keeps provision for tuning of membership functions using recent data from the given time-series to influence the prediction results with the current trends. Experiments undertaken confirm that the fourth technique outperforms the first three techniques and also the existing techniques with respect to root-mean-square error metric.

A Comparison of Cost Partitioning Algorithms for Optimal Classical Planning

Cost partitioning is a general and principled approach for constructing additive admissible heuristics for state-space search. Cost partitioning approaches for optimal classical planning include optimal cost partitioning, uniform cost partitioning, zero-one cost partitioning, saturated cost partitioning, post-hoc optimization and the canonical heuristic for pattern databases. We compare these algorithms theoretically, showing that saturated cost partitioning dominates greedy zero-one cost partitioning. As a side effect of our analysis, we obtain a new cost partitioning algorithm dominating uniform cost partitioning. We also evaluate these algorithms experimentally on pattern databases, Cartesian abstractions and landmark heuristics, showing that saturated cost partitioning is usually the method of choice on the IPC benchmark suite.

New content‐based image retrieval system based on optimised integration of DCD, wavelet and curvelet features

A new content-based image retrieval (CBIR) scheme is proposed based on the optimised combination of the colour and texture features to enhance the image retrieval precision. This work focuses on a uniform partitioning scheme which is applied in the Hue, Saturation and Value (HSV) colour space to extract dominant colour descriptor (DCD) features. In the proposed CBIR scheme, the DCD features are initially extracted as the colour features, and then an appropriate similarity measure is applied. Also, several wavelet and curvelet features are defined as texture features to overcome the noise and the problem of image translation. Finally, the colour and texture features are optimally combined by using the particle swarm optimisation algorithm. The findings show that not only the proposed colour, wavelet and curvelet features outperform the existing ones but also their optimum combination has a better accuracy in comparison with several contemporary CBIR systems. The performance analysis shows that the proposed method improves the average precision metric from 67.85 to 71.05% for DCD, 58.90 to 65.43% for wavelet and 53.18 to 56.00% for curvelet using Corel dataset. In addition, the optimum combination presents the average precision of %76.50 which is significantly higher than the other state-of-the-art methods.

Uniform hypergraph partitioning

In a series of recent works, we have generalised the consistency results in the stochastic block model literature to the case of uniform and non-uniform hypergraphs. The present paper continues the...

Resource bricolage and resource selection for parallel database systems

Running parallel database systems in an environment with heterogeneous resources has become increasingly common, due to cluster evolution and increasing interest in moving applications into public clouds. Performance differences among machines in the same cluster pose new challenges for parallel database systems. First, for database systems running in a heterogeneous cluster, the default uniform data partitioning strategy may overload some of the slow machines, while at the same time it may underutilize the more powerful machines. Since the processing time of a parallel query is determined by the slowest machine, such an allocation strategy may result in a significant query performance degradation. Second, since machines might have varying resources or performance, different choices of machines may lead to different costs or performance for executing the same workload. By carefully selecting the most suitable machines for running a workload, we may achieve better performance with the same budget, or we may meet the same performance requirements with a lower cost. We address these challenges by introducing techniques we call resource bricolage and resource selection that improve database performance in heterogeneous environments. Our approaches quantify the performance differences among machines with various resources as they process workloads with diverse resource requirements. For the purpose of better resource utilization, we formalize the problem of minimizing workload execution time and view it as an optimization problem, and then, we employ linear programming to obtain a recommended data partitioning scheme. For the purpose of better resource selection, we formalize two problems: One minimizes the total workload execution time with a given budget, and the other minimizes the total budget with a given performance target. We then employ different mixed-integer programs to search for the optimal resource selection decisions. We verify the effectiveness of both resource bricolage and resource selection techniques with an extensive experimental study.

Mechanisms of Simultaneous Hydraulic-Fracture Propagation From Multiple Perforation Clusters in Horizontal Wells

Summary Simultaneous multiple-fracture treatments in horizontal wellbores are becoming a prevalent approach to economically develop unconventional resources in shale reservoirs. One challenge to efficiently use the technique is the generation of effective hydraulic fractures from all perforation clusters. In this work, we conducted a fundamental study of physical mechanisms controlling simultaneous multiple-fracture propagation and discussed the potential approaches to improve nonuniform development of multiple fractures. This study was investigated by our recently developed 3D fracture-propagation model that captures the coupled elastic deformation of the rock with fluid flow in the horizontal wellbore and within the fractures. The model demonstrated that fracture geometry was controlled by both the stress-shadow effects and dynamic partitioning of flow rate. The analysis results indicated that the nonuniform development of a multiple-fracture array, for example, a three-fracture array in this study, was induced by the uneven partitioning of flow rate into each fracture, which was dependent on the flow resistance from wellbore friction, perforation friction, and fracture propagation. Furthermore, the stress shadowing from the exterior fractures exerted additional stress on the interior fractures and increased the resistance of fracture propagation, resulting in the interior fractures receiving much less fluid. To minimize the negative effects of stress shadowing and favor more-uniform fracture growth, we investigated potential approaches to promote uniform partitioning of flow rate through adjusting the flow resistance between multiple fractures. The results showed that adjusting perforation friction can provide an effective way to modify the partitioning of flow rate and mitigate the negative effects of stress shadowing. The mechanisms investigated in this study are consistent with field observations. Our approach can help field operators to improve the effectiveness of multiple fracturing treatments and maximize the production.

Resource Bricolage for Parallel DBMSs on Heterogeneous Clusters

Running parallel database systems in an environment with heterogeneous resources has become increasingly common, due to cluster evolution and increasing interest in moving applications into public clouds or shared infrastructures. For database systems running in a heterogeneous cluster, the default uniform data partitioning strategy may overload some of the slow machines while at the same time it may underutilize the more powerful machines. Since the processing time of a parallel query is determined by the slowest machine, such an allocation strategy may result in a significant query performance degradation. We take a first step to address this problem by introducing a technique we call resource bricolage that improves database performance in heterogeneous environments. Our approach quantifies the performance differences among machines with various resources as they process workloads with diverse resource requirements. We formalize the problem of minimizing workload execution time and view it as an optimization problem, and then we employ linear programming to obtain a recommended data partitioning scheme. We verify the effectiveness of our technique with an extensive experimental study on a commercial database system.