A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

Dynamic Job Scheduling on the Grid Environment using the Great Deluge Algorithm

The utilization of the computational Grid processor network has become a common method for researchers and scientists without access to local processor clusters to avail of the benefits of parallel processing for compute-intensive applications. As a result, this demand requires effective and efficient dynamic allocation of available resources. Although static scheduling and allocation techniques have proved effective, the dynamic nature of the Grid requires innovative techniques for reacting to change and maintaining stability for users. The dynamic scheduling process requires quite powerful optimization techniques, which can themselves lack the performance required in reaction time for achieving an effective schedule solution. Often there is a trade-off between solution quality and speed in achieving a solution. This paper presents an extension of a technique used in optimization and scheduling which can provide the means of achieving this balance and improves on similar approaches currently published.

Neuromuscular adaptation during skill acquisition on a two degree-of-freedom target-acquisition task: Dynamic movement

In this experiment, we examined the extent to which the spatiotemporal reorganization of muscle synergies mediates skill acquisition on a two degree-of-freedom (df) target-acquisition task. Eight participants completed five practice sessions on consecutive days. During each session they practiced movements to eight target positions presented by a visual display. The movements required combinations of flexion/extension and pronation/supination of the elbow joint complex. During practice sessions, eight targets displaced 5.4 cm from the start position ( representing joint excursions of 54) were presented 16 times. During pre- and posttests, participants acquired the targets at two distances (3.6 cm [36 degrees] and 7.2 cm [72 degrees]). EMG data were recorded from eight muscles contributing to the movements during the pre- and posttests. Most targets were acquired more rapidly after the practice period. Performance improvements were, in most target directions, accompanied by increases in the smoothness of the movement trajectories. When target acquisition required movement in both dfs, there were also practice-related decreases in the extent to which the trajectories deviated from a direct path to the target. The contribution of monofunctional muscles ( those producing torque in a single df) increased with practice during movements in which they acted as agonists. The activity in bifunctional muscles ( those contributing torque in both dfs) remained at pretest levels in most movements. The results suggest that performance gains were mediated primarily by changes in the spatial organization of muscles synergies. These changes were expressed most prominently in terms of the magnitude of activation of the monofunctional muscles.

The impact of the summer 2007 forest fires in Greece: Recent environmental mobilizations, cyber-activism and electoral performance

This report circumambulates around the environmental issue, examining mobilizations in favour of public access to the seafront and protest events against the recent devastating forest fires. By framing this discussion within existing scholarly contributions on related dimensions of the environmental issue (environmental consciousness, grassroots environmental contestation) in Southern Europe in general and Greece in particular, it suggests that the environmental mobilization dynamic in Greece has been infused with a new, global, mobilizing resource that offers new avenues to evaluate the potency of Greek civil society. Finally, the article discusses the results of the 2007 national elections and ponders the chances of political ecology becoming a permanent feature of Greek parliamentary politics.

Do dynamic work instructions provide an advantage over static instructions in a small scale assembly task?

Recent studies exploring the effects of instructional animations on learning compared to static graphics have yielded mixed results. Few studies have explored their effectiveness in portraying procedural-motor information. Opportunities exist within an applied (manufacturing) context for instructional animations to be used to facilitate build performance on an assembly line. The present study compares build time performance across successive builds when using animation, static diagrams or text instructions to convey an assembly sequence for a handheld device. Although an immediate facilitating effect of animation was found, yielding a significantly faster build time for Build 1, this advantage had disappeared by Build 3. (C) 2009 Elsevier Ltd. All rights reserved.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

Deformation of titanium alloy Ti-6Al-4V under dynamic compression

Deformation localisation is the main reason for material failure in cold forging of titanium alloys and is thus closely related to the production yield of cold forging. In the study of the influence of process parameters on dynamic compression, considering material constitutive behaviour, physical parameters and process parameters, a numerical dynamic compression model for titanium alloys has been constructed. By adjusting the process parameters, the severity of strain localisation and stress state in the localised zone can be controlled thus enhancing the compression performance of titanium alloys.

Dynamic Linear Precoding for the Exploitation of Known Interference in MIMO Broadcast Systems

This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

A Theoretical and Experimental Study of Resonance in a High Performance Engine Intake System: Part 1

The unsteady gas dynamic phenomena in engine intake systems of the type found in racecars have been examined. In particular, the resonant tuning effects, including cylinder-to-cylinder power variations, which can occur as a result of the interaction between an engine and its airbox have been considered. Frequency analysis of the output from a Virtual 4-Stroke 1D engine simulation was used to characterise the forcing function applied by an engine to an airbox. A separate computational frequency sweeping technique, which employed the CFD package FLUENT, was used to determine the natural frequencies of virtual airboxes in isolation from an engine. Using this technique, an airbox with a natural frequency at 75 Hz was designed for a Yamaha R6 4-cylinder motorcycle engine. The existence of an airbox natural frequency at 75 Hz was subsequently confirmed by an experimental frequency sweeping technique carried out on the engine test bed. A coupled 1D/3D analysis which employed the engine simulation package Virtual 4-Stroke and the CFD package FLUENT, was used to model the combined engine and airbox system. The coupled 1D/3D analysis predicted a 75 Hz resonance of the airbox at an engine speed of 9000 rpm. This frequency was the induction frequency for a single cylinder. An airbox was fabricated and tested on the engine. Static pressure was recorded at a grid of points in the airbox as the engine was swept through a speed range of 3000 to 10000 rpm. The measured engine speed corresponding to resonance in the airbox agreed well with the predicted values. There was also good correlation between the amplitude and phase of the pressure traces recorded within the airbox and the 1D/3D predictions.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Performance of Unsaturated Compacted Clay Under Repeated Loading Effects of Confining Pressure, Initial Compaction Effort and Water Content

While a significant number of geotechnical structures are subjected to static loading, many, such as avement subgrade, also are subjected to cyclic or dynamic loading. While the performance of saturated soils under repeated, cyclic or dynamic loading conditions is still a topic of research, similar interests are growing when the soilcondition is unsaturated. This paper examines the performance of unsaturated soils under repeated loading. As part of the research, a triaxial system was developed which incorporates small strain measurements using Hall-effect transducers, in addition to suction measurements taken using a psychrometer. Tests were conducted on samples of kaolin under constant water mass conditions. The results address the effects of compaction effort and water content at the time of compaction on the overall performance of unsaturated soils, under different amplitudes of loading and different confining pressures. The results show that suction in the sample reduced with increasing number of loading cycles of the same magnitude. The resilient modulus initially increased with increasing water content up to approximately optimum water content, and substantially reduced with further increase in water content. Key Words: suction, resilient modulus, subgrade, repeated loading, small strain measurements, compaction.

A Dynamic Factor Approach to Mortality Modelling

Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors. 

Minimizing side reactions in chemoenzymatic dynamic kinetic resolution: organometallic and material strategies

Chemoenzymatic dynamic kinetic resolution (DKR) of rac-1-phenyl ethanol into R-1-phenylethanol acetate was investigated with emphasis on the minimization of side reactions. The organometallic hydrogen transfer (racemization) catalyst was varied, and this was observed to alter the rate and extent of oxidation of the alcohol to form ketone side products. The performance of highly active catalyst [(pentamethylcyclopentadienyl) IrCl2(1-benzyl,3-methyl-imidazol-2-ylidene)] was found to depend on the batch of lipase B used. The interaction between the bio- and chemo-catalysts was reduced by employing physical entrapment of the enzyme in silica using a sol-gel process. The nature of the gelation method was found to be important, with an alkaline method preferred, as an acidic method was found to initiate a further side reaction, the acid catalyzed dehydration of the secondary alcohol. The acidic gel was found to be a heterogeneous solid acid.