Hierarchical Reduction Research Articles

A visual LISP program for voxelizing AutoCAD solid models

AutoCAD solid models are increasingly recognized in geological and geotechnical 3D modeling. In order to bridge the currently existing gap between AutoCAD solid models and the grid modeling realm, a Visual LISP program is presented that converts AutoCAD solid models into voxel arrays. Acad2Vox voxelizer works on a 3d-model that is made up of arbitrary non-overlapping 3D-solids. After definition of the target voxel array geometry, 3D-solids are scanned at grid positions and properties are streamed to an ASCII output file. Acad2Vox has a novel voxelization strategy that combines a hierarchical reduction of sampling dimensionality with an innovative use of AutoCAD-specific methods for a fast and memory-saving operation. Acad2Vox provides georeferenced, voxelized analogs of 3D design data that can act as regions-of-interest in later geostatistical modeling and simulation. The Supplement includes sample geological solid models with instructions for practical work with Acad2Vox.

Alcohol Ingestion Impairs Maximal Post-Exercise Rates of Myofibrillar Protein Synthesis following a Single Bout of Concurrent Training

IntroductionThe culture in many team sports involves consumption of large amounts of alcohol after training/competition. The effect of such a practice on recovery processes underlying protein turnover in human skeletal muscle are unknown. We determined the effect of alcohol intake on rates of myofibrillar protein synthesis (MPS) following strenuous exercise with carbohydrate (CHO) or protein ingestion.MethodsIn a randomized cross-over design, 8 physically active males completed three experimental trials comprising resistance exercise (8×5 reps leg extension, 80% 1 repetition maximum) followed by continuous (30 min, 63% peak power output (PPO)) and high intensity interval (10×30 s, 110% PPO) cycling. Immediately, and 4 h post-exercise, subjects consumed either 500 mL of whey protein (25 g; PRO), alcohol (1.5 g·kg body mass−1, 12±2 standard drinks) co-ingested with protein (ALC-PRO), or an energy-matched quantity of carbohydrate also with alcohol (25 g maltodextrin; ALC-CHO). Subjects also consumed a CHO meal (1.5 g CHO·kg body mass−1) 2 h post-exercise. Muscle biopsies were taken at rest, 2 and 8 h post-exercise.ResultsBlood alcohol concentration was elevated above baseline with ALC-CHO and ALC-PRO throughout recovery (P<0.05). Phosphorylation of mTORSer2448 2 h after exercise was higher with PRO compared to ALC-PRO and ALC-CHO (P<0.05), while p70S6K phosphorylation was higher 2 h post-exercise with ALC-PRO and PRO compared to ALC-CHO (P<0.05). Rates of MPS increased above rest for all conditions (∼29–109%, P<0.05). However, compared to PRO, there was a hierarchical reduction in MPS with ALC-PRO (24%, P<0.05) and with ALC-CHO (37%, P<0.05).ConclusionWe provide novel data demonstrating that alcohol consumption reduces rates of MPS following a bout of concurrent exercise, even when co-ingested with protein. We conclude that alcohol ingestion suppresses the anabolic response in skeletal muscle and may therefore impair recovery and adaptation to training and/or subsequent performance.

Hierarchical coarse-graining model for photosystem II including electron and excitation-energy transfer processes

We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics.

The Attribute of Compatibility between the Process of Organization and the Function of Human Resources

The evolution of the organizational forms has seen quite dynamic in recent years, registered trends being observed in the enterprise subsystems. The human resources function, a subsystem in continuous development since the 1990s, is subjected to changes such as decentralization, hierarchical reduction and resizing, as a consequence of its missions delegation both inside and outside the organization. Approach: These changes are exacerbated by the emergence of new techniques of information and communication (NTIC), which change the context in which human resources function evolves. The need to adapt the development of human resources function to the enterprises’ strategy causes a strategic alignment requirement. Results: The functions' content will also be modified, in the direction of what may designate e-Human Resources, characterized by the increasing role of the Intranet, the use of the NTIC in supporting activities such as e-recruiting and e-learning. Conclusion/Recommendations: The article highlights the need for consistency between the process of organization and the function of human resources, the necessary compatibility in the sense that it is not possible to examine the evolution of an enterprise independent of the characteristics of the enterprises the organization is part of.

Coupled Model and Grid Adaptivity in Hierarchical Reduction of Elliptic Problems

In this paper we propose a surrogate model for advection---diffusion---reaction problems characterized by a dominant direction in their dynamics. We resort to a hierarchical model reduction where we couple a modal representation of the transverse dynamics with a finite element approximation along the mainstream. This different treatment of the dynamics entails a surrogate model enhancing a purely 1D description related to the leading direction. The coefficients of the finite element expansion along this direction introduce a generally non-constant description of the transversal dynamics. Aim of this paper is to provide an automatic adaptive approach to locally select the dimension of the modal expansion as well as the finite element step in order to satisfy a prescribed tolerance on a goal functional of interest.

Intrinsic Bayesian model for high-dimensional unsupervised reduction

This paper proposes a novel algorithm for high-dimensional unsupervised reduction from intrinsic Bayesian model. The proposed algorithm is to assume that the pixel reflectance results from nonlinear combinations of pure component spectra contaminated by additive noise. The constraints are naturally expressed in intrinsic Bayesian literature by using appropriate abundance prior distributions. The posterior distributions of the unknown model parameters are then derived. The proposed algorithm consists of intrinsic Bayesian inductive cognition part and hierarchical reduction algorithm model part. The algorithm has several advantages over traditional distance based on Bayesian reduction algorithms. The proposed reduction algorithm from intrinsic Bayesian inductive cognitive model is used to decide which dimensions are advantageous and to output the recommended dimensions of the hyperspectral image. The algorithm can be interpreted as a novel fast reduction inference method for intrinsic Bayesian inductive cognitive model. We describe procedures for learning the model hyperparameters, computing the dimensions distribution, and extensions to the intrinsic Bayesian inductive cognition model. Experimental results on hyperspectral data demonstrate robust and useful properties of the proposed reduction algorithm.

Hepatic steatosis, GH deficiency and the effects of GH replacement: a Liverpool magnetic resonance spectroscopy study

Non-alcoholic fatty liver disease (NAFLD) is reported to be more common in patients with GH deficiency (GHD) than in the general population. we aimed to determine: i) liver fat in patients with GHD compared with age and body mass index (BMI)-matched controls; and ii) effect of 6 months of GH replacement (GHR) on liver fat. The study included 28 GHD patients and 24 controls. 12 patients were studied before and after 6 months of GHR. Anthropometry, liver enzymes and lipid profiles were measured, and body composition and intrahepatocellular lipid (IHCL) were determined by magnetic resonance imaging and spectroscopy. Age and BMI (median (inter-quartile range)) of patients and controls were 52.6 (14) vs 52.6 (12) years (P=0.9) and 27.8 (24.7, 34.7) vs 27.9 (25.1, 32.1) kg/m(2) (P=0.9). IGF1 was lower in the patients (11.5 vs 16.0 nmol/l, P=0.002). There was no difference in liver transaminases, lipids or IHCL between patients and controls (2.8 (1.3, 8.6) vs 5.0 (1.5, 12.7), P=0.72), despite significantly higher visceral fat in GHD patients. Thirty-two percent of patients and 50% of controls had NAFLD (defined as IHCL >5.6%), and the relationship between IHCL and BMI was the same in each group. GHR significantly reduced abdominal subcutaneous and visceral fat in all patients; however, GHR did not reduce liver fat. NAFLD is equally common in patients with GHD and matched controls. GHR is associated with a hierarchical reduction in fat deposition (fat loss: visceral > subcutaneous > liver). Further studies involving GHD patients with NAFLD are required to conclude the role of GHR in treating NAFLD.

Simple stone flaking in Australasia: Patterns and implications

The archaeological records in the Old World and Australasia reflect a pattern of simple approaches to stone flaking in early stone tool assemblages followed by a later proliferation in more complex approaches. Although the pattern is similar in structure, the proliferation of complex flaking occurred much later in Australasia. ‘Simple’ stone flaking can be characterized as the arrangement of flake removals in chains and ‘complex’ approaches involved a hierarchical arrangement. Some archaeologists see the proliferation of hierarchical reduction sequences as a reflection of hominin cognitive changes, but Homo sapiens colonizers of Australia—carrying a toolkit made by simple chaining—were cognitively modern. The Australian proliferation has been explained as a response to ecological conditions but this proximate explanation fails to account for the complex nature of hierarchical reduction sequences. Demographic modeling that links the emergence of complex stone flaking to population structure or growth better accounts for the proliferations in both the Old World and Australasia. Efforts to reconstruct hominin migrations through Asia by focusing on the ‘derived’ parts of stone toolkits track demographically-linked trends rather than initial emigration events.

Reduction of a detailed kinetic model for the ignition of methane/propane mixtures at gas turbine conditions using simulation error minimization methods

Natural gas is the primary fuel for industrial gas turbines, which provide about one quarter of the world’s primary energy supply. Beside methane it also contains larger hydrocarbons in small, varying ratios. This variation is expected to rise due to the increasing usage of non-traditional gas sources. Fuel composition has a large impact on auto-ignition delay time, which is a fundamental parameter for the optimal design and operation of gas turbines. For the oxidation of such mixtures, Curran, Petersen and co-workers recently developed a detailed reaction mechanism (NUIG NGM), which reproduces the ignition delays over a wide range of conditions. However, due to its large size: 229 species and 1359 reactions, it cannot be used in computational fluid dynamics simulations, which is an important fundamental tool in the development of gas turbines. A mechanism reduction case study of the NUIG NGM is presented using the recently developed simulation error minimization methods (SEM). A new version of the SEM program package is also proposed, which allows the reduction of mechanisms for a wider range of combustion phenomena. Combinational strategies have been introduced in the SEM connectivity method to enhance the reduction procedure and a hierarchical reduction procedure is proposed for multi-scenario problems. Ignition of lean and stoichiometric mixtures containing 90% methane and 10% propane as fuel were investigated for 22 conditions relevant to gas turbines, covering temperature and pressure ranges of 877–1465 K and 7–40 atm, respectively. The smallest reduced mechanism developed contains 50 species and 186 reactions. It can reproduce ignition delays with 3.1% maximum error and reproduces pressure rise precisely (error∼10 −3%). The mechanism can be simulated 62 times faster than the full mechanism. Robustness analysis showed that it is reliably applicable over a much wider range of conditions compared to that for which it was developed.

A Robust High-dimensional Data Reduction Method

In this paper, we propose a robust high-dimensional data reduction method. The model assumes that the pixel reflec-tance results from linear combinations of pure component spectra contaminated by an additive noise. The abundance parameters appearing in this model satisfy positivity and additive constraints. These constraints are naturally expressed in a Bayesian literature by using appropriate abundance prior distributions. The posterior distributions of the unknown model parameters are then derived. The proposed algorithm consists of Bayesian inductive cognition part and hierarchical reduction algorithm model part. The pro-posed reduction algorithm based on Bayesian inductive cognitive model is used to decide which dimensions are advantageous and to output the recommended dimensions of the hyperspectral image. The algorithm can be interpreted as a robust reduction inference method for a Bayesian inductive cognitive model. Experimental results on high-dimensional data demonstrate useful properties of the proposed reduction algorithm.

Hierarchical Reduction Method of Protein Structures for Understanding Protein Dynamics

Understanding protein dynamics is prerequisite for investigating the biological functions of proteins. Protein Dynamics has been understood based on atomistic model for protein structure. However, atomistic model has been computationally limited for large protein dynamics. In this talk, we address how to computationally solve the large protein dynamics problem by implementing the component mode synthesis method which allows the computations on low-frequency modes of large proteins. Specifically, component mode synthesis allows us to consider the vibration motion of each protein domain instead of whole protein structure, and then the dynamic characterization of each domain is assembled to provide the insight into dynamics of whole protein structure. (see Fig. 1) Hemoglobin was chosen as one of the model proteins in present study. Fig. 2(a) represents Hemoglobin model, Fig. 2(b) displays constraint points at boundaries between adjacent components. The mean-square fluctuations of model proteins are compared by both GNM and component mode synthesis in Fig. 3. It is remarkable that component mode synthesis provides the mean-square fluctuation qualitatively comparable to the one obtained by both GNM and experiment one, even though component allows one to reduce the computational burden on the mean-square fluctuation.This suggests that the proposed method may allow for gaining insight into dynamics of supramolecules with computational efficiency.Fig. 1. Configuration of a structure with components(a) Hemoglobin(pdb code: 1a3n)(b) Constraint points (dotted points) and four components (different colors)Fig. 2 Hemoglobin target modelFig. 3 Comparison of mean square fluctuation of X-ray crystallography, GNM modeling and component mode synthesis.

Hierarchical Krylov subspace based reduction of large interconnects

In this paper, we propose a new model order reduction approach for large interconnect circuits using hierarchical decomposition and the Krylov subspace projection-based model order reduction methods. The new approach, called hiePrimor, first partitions a large interconnect circuit into a number of smaller subcircuits and then performs the projection-based model order reduction on each of subcircuits in isolation and on the top-level circuit thereafter. The new approach is very amenable for exploiting the multi-core based parallel computing platforms to significantly speed up the reduction process. Theoretically we show that hiePrimor can deliver the same accuracy as the flat reduction method given the same reduction order and it can also preserve the passivity of the reduced models as well. We also show that partitioning has large impacts on the performance of hierarchical reduction and the minimum-span objective should be required to attain the best performance for hierarchical reduction. The proposed method is suitable for reducing large global interconnects like coupled bus, transmission lines, large clock nets in the post-layout stage. Experimental results demonstrate that hiePrimor can be significantly faster and more scalable than the flat projection methods like PRIMA and be order of magnitude faster than PRIMA with parallel computing without loss of accuracy. Interconnect circuits with up to 4 million nodes can be analyzed in a few minutes even in Matlab by the new method.

Wideband passive multiport model order reduction and realization of RLCM circuits

This paper presents a novel compact passive modeling technique for high-performance RF passive and interconnect circuits modeled as high-order resistor-inductor-capacitor-mutual inductance circuits. The new method is based on a recently proposed general s-domain hierarchical modeling and analysis method and vector potential equivalent circuit model for self and mutual inductances. Theoretically, this paper shows that s-domain hierarchical reduction is equivalent to implicit moment matching at around s=0 and that the existing hierarchical reduction method by one-point expansion is numerically stable for general tree-structured circuits. It is also shown that hierarchical reduction preserves the reciprocity of passive circuit matrices. Practically, a hierarchical multipoint reduction scheme to obtain accurate-order reduced admittance matrices of general passive circuits is proposed. A novel explicit waveform-matching algorithm is proposed for searching dominant poles and residues from different expansion points based on the unique hierarchical reduction framework. To enforce passivity, state-space-based optimization is applied to the model order reduced admittance matrix. Then, a general multiport network realization method to realize the passivity-enforced reduced admittance based on the relaxed one-port network synthesis technique using Foster's canonical form is proposed. The resulting modeling algorithm can generate the multiport passive SPICE-compatible model for any linear passive network with easily controlled model accuracy and complexity. Experimental results on an RF spiral inductor and a number of high-speed transmission line circuits are presented. In comparison with other approaches, the proposed reduction is as accurate as passive reduced-order interconnect macromodeling algorithm in the high-frequency domain due to the enhanced multipoint expansion, but leads to smaller realized circuit models. In addition, under the same reduction ratio, realized models by the new method have less error compared with reduced circuits by time-constant-based reduction techniques in time domain.

A monotonic and positive–definite filter for a Semi‐Lagrangian Inherently Conserving and Efficient (SLICE) scheme

AbstractA new monotonic and positive–definite filter is incorporated into an existing Semi‐Lagrangian Inherently Conserving and Efficient (SLICE) scheme for transport problems in both Cartesian and spherical geometry. The SLICE scheme is based on a control‐volume approach that uses multiple sweeps of a one‐dimensional O (Δx4) conservation remapping algorithm along predetermined cascade directions. The new filter combines a selective detection algorithm, to pinpoint regions of non‐monotonic behaviour, with a hierarchical reduction of the degree of the piecewise reconstruction in such regions, to re‐establish monotonicity. The enhanced, monotonic and positive–definite, SLICE scheme is tested in one dimension, and then applied to standard two‐dimensional test problems in both Cartesian and spherical geometries. Comparisons with published results of other conservative semi‐Lagrangian schemes show that it performs well. © Crown copyright, 2005.

Software pipelining

The basic idea behind software pipelining was first developed by Patel and Davidson for scheduling hardware pipe-lines. As instruction-level parallelism made its way into general-purpose computing, it became necessary to automate scheduling. How and whether instructions can be scheduled statically have major ramifications on the design of computer architectures. Rau and Glaeser were the first to use software pipelining in a compiler for a machine with specialized hardware designed to support software pipelining. In the meantime, trace scheduling was touted to be the scheduling technique of choice for VLIW (Very Long Instruction Word) machines. The most important contribution from this paper is to show that software pipelining is effective on VLIW machines without complicated hardware support. Our understanding of software pipelining subsequently deepened with the work of many others. And today, software pipelining is used in all advanced compilers for machines with instruction-level parallelism, none of which, except the Intel Itanium, relies on any specialized support for software pipelining.This paper shows that software pipelining is an effective and viable scheduling technique for VLIW processors. In software pipelining, iterations of a loop in the source program are continuously initiated at constant intervals, before the preceding iterations complete. The advantage of software pipelining is that optimal performance can be achieved with compact object code.This paper extends previous results of software pipelining in two ways: First, this paper shows that by using an improved algorithm, near-optimal performance can be obtained without specialized hardware. Second, we propose a hierarchical reduction scheme whereby entire control constructs are reduced to an object similar to an operation in a basic block. With this scheme, all innermost loops, including those containing conditional statements, can be software pipelined. It also diminishes the start-up cost of loops with small number of iterations. Hierarchical reduction complements the software pipelining technique, permitting a consistent performance improvement be obtained.The techniques proposed have been validated by an implementation of a compiler for Warp, a systolic array consisting of 10 VLIW processors. This compiler has been used for developing a large number of applications in the areas of image, signal and scientific processing.

712 Hierarchical Recursive PIV methodによる噴流の渦構造の可視化(オーガナイズドセッション7 流れの可視化応用解析)

Hierarchical Recursive PIV (HR-PIV) method, which can get a very high spatial resolution compared with conventional PIV image processing methods, was used to do PIV image processing of a jet mixing flow. By starting with a large interrogation window size and search distance as the same as conventional correlation analysis based PIV image processing methods, HR-PIV method improved the spatial resolution of the PIV result through hierarchical reduction of the interrogation window size and search distance in the next iteration step by using the calculation results of former step. It was found that the small scale vortices and turbulent structures in a jet mixing flow, which can not be identified by using conventional PIV image processing methods, can be revealed very clearly by using Hierarchical Recursive PIV (HR-PIV) method

Register Allocation—A Hierarchical Reduction Approach

A new approach to the problem of register allocation in high-level synthesis is presented. The algorithm employs a bottom-up transformational approach--sets of mutually exclusive variables in conditional branches are transformed into an "equivalent" set of nonmutually exclusive variables. The transformational approach is extended to the case of data-flow graphs with loops. A new register allocation algorithm is then used to produce an allocation for the nonmutually exclusive variables. From such an allocation, a corresponding allocation for the original set of mutually exclusive variables is derived. Our approach is particularly effective when there is a large number of nested conditional branches and loops in a data-flow graph.

Hierarchical reduction and partition of hypergraph

In this paper, a hierarchical reduction method of hypergraphs is proposed. A macro-vertex in a reduced hypergraph corresponds to an edge of the original hypergraph, and thus a reduced hypergraph can provide a partition of a system. The reduction is realized by the iterations and the sequence of hierarchical reduction gives a sequence of hierarchical partitions. The proposed method allows to reduce and decompose the complexity of the system represented by hypergraphs.

A scheduling algorithm for conditional resource sharing-a hierarchical reduction approach

A new scheduling algorithm for dataflow graphs with nested conditional branches is presented. The algorithm employs a bottom-up approach to transform a dataflow graph with conditional branches into an "equivalent" one that has no conditional branches. A schedule is then obtained for the latter, using a conventional scheduling algorithm, from which a schedule for the former is derived. Our approach is particularly effective when there is a large number of nested conditional branches in a dataflow graph.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Computer-based reduction technique for Petri nets

Petri nets have become a useful tool for modelling various classes of system, especially concurrent systems. A Petri net model for a real-life system may become quite large in dimension (having a large number of reachable states and events) and it becomes quite difficult to analyse the net. In such a situation, a large net is reduced to nets and subnets of lower dimension (wherein desirable properties are preserved) which are subsequently analysed. The present paper proposes a computer-oriented hierarchical reduction technique for Petri nets utilizing a recently proposed reflexive incidence matrix representation. Given the incidence matrix representation of the net, the associated software developed for this purpose performs step-by-step reduction and produces a reduced net of smaller dimension suitable for analysis and related tasks.