Improved kinematic sensing for motion control applications

New compensation methods are presented that can greatly reduce the slit errors (i.e. transition location errors) and interval errors induced due to non-idealities in optical incremental encoders (square-wave). An M/T-type, constant sample-time digital tachometer (CSDT) is selected for measuring the velocity of the sensor drives. Using this data, three encoder compensation techniques (two pseudoinverse based methods and an iterative method) are presented that improve velocity measurement accuracy. The methods do not require precise knowledge of shaft velocity. During the initial learning stage of the compensation algorithm (possibly performed in-situ), slit errors/interval errors are calculated through pseudoinversebased solutions of simple approximate linear equations, which can provide fast solutions, or an iterative method that requires very little memory storage. Subsequent operation of the motion system utilizes adjusted slit positions for more accurate velocity calculation. In the theoretical analysis of the compensation of encoder errors, encoder error sources such as random electrical noise and error in estimated reference velocity are considered. Initially, the proposed learning compensation techniques are validated by implementing the algorithms in MATLAB software, showing a 95% to 99% improvement in velocity measurement. However, it is also observed that the efficiency of the algorithm decreases with the higher presence of non-repetitive random noise and/or with the errors in reference velocity calculations. The performance improvement in velocity measurement is also demonstrated experimentally using motor-drive systems, each of which includes a field-programmable gate array (FPGA) for CSDT counting/timing purposes, and a digital-signal-processor (DSP). Results from open-loop velocity measurement and closed-loop servocontrol applications, on three optical incremental square-wave encoders and two motor drives, are compiled. While implementing these algorithms experimentally on different drives (with and without a flywheel) and on encoders of different resolutions, slit error reductions of 60% to 86% are obtained (typically approximately 80%).

Enhancing an Incremental Clustering Algorithm for Web Page Collections

With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Incremental entrepreneurship : best practice professionalization across generations

This chapter will introduce Australia’s Dennis family – a case of ‘incremental entrepreneurship’ in the business transition from the first to the second generation. Following the second generation’s formal involvement and ownership in the business, Dennis Family Corporation (DFC) undertook a major professionalization process to formalize the family business and ensure its continued success. The members of the second generation have successfully sustained the entrepreneurial spirit of their family business (albeit in a different style), adding value to the firm in an ‘incremental’ manner. Throughout the chapter there will be a strong emphasis on the family element of DFC and the roles that each family member has played. Bert Dennis, as the founder and incumbent leader of the firm, has witnessed major changes to the business he built from the ground up. His children, in particular his son Grant Dennis as the primary next generation issue champion, have seen the changes from another perspective – ensuring the business remains within the family into the second generation and beyond. The professionalization process was sparked by a commitment from the second generation to continue to ‘make a real go’ of the family business rather than simply liquidating and distributing the assets. The dedication of all the family members to this objective has ensured the success of this process, and ultimately, the longevity of the firm. Although DFC has become more ‘professional’, it has not lost its entrepreneurial character; rather, it has improved the ways in which entrepreneurialism is fostered and pursued in the company. In essence, this case outlines how the implementation of appropriate governance and management practices has allowed the Dennis family to overcome the challenges and maximize the opportunities associated with owning and operating a multigenerational family fi rm. From a theoretical perspective, this case uses the concepts of entrepreneurial orientation (EO) (Lumpkin and Dess 1996) and the resource- based view (RBV) (Habbershon and Williams 1999; Barney 1991; Wernerfelt 1984) to demonstrate how the fi rm has leveraged its familiness to foster an enduring spirit of entrepreneurship and to maintain a sustained competitive advantage.

Managing open incremental process innovation : absorptive capacity and distributed learning

In this conceptual article, we extend earlier work on Open Innovation and Absorptive Capacity. We suggest that the literature on Absorptive Capacity does not place sufficient emphasis on distributed knowledge and learning or on the application of innovative knowledge. To accomplish physical transformations, organisations need specific Innovative Capacities that extend beyond knowledge management. Accessive Capacity is the ability to collect, sort and analyse knowledge from both internal and external sources. Adaptive Capacity is needed to ensure that new pieces of equipment are suitable for the organisation's own purposes even though they may have been originally developed for other uses. Integrative Capacity makes it possible for a new or modified piece of equipment to be fitted into an existing production process with a minimum of inessential and expensive adjustment elsewhere in the process. These Innovative Capacities are controlled and coordinated by Innovative Management Capacity, a higher-order dynamic capability.

Mainstreaming climate change adaptation : An incremental approach to disaster risk management in Australia

In this paper we argue that rationalist ‘predict then act’ approaches to disaster risk management (DRM) policy promote unrealistic public expectations of DRM provisions, the avoidance of decision making by political elites, an over-reliance on technical expertise and engineering solutions to reducing exposure to natural events, and a reactive approach to DRM overall. We propose an alternative incrementalist approach that focuses on managing uncertainties rather than reducing them and building resilience not simply through the reduction of hazard exposure, but also through the ongoing reduction of community vulnerability, the explicit consideration of normative priorities, and more effective community engagement in climate risk debates.

User perceived video quality modelling on mobile devices for Vp9 and H265 encoders

This study constructs performance prediction models to estimate the end-user perceived video quality on mobile devices for the latest video encoding techniques –VP9 and H.265. Both subjective and objective video quality assessments were carried out for collecting data and selecting the most desirable predictors. Using statistical regression, two models were generated to achieve 94.5% and 91.5% of prediction accuracies respectively, depending on whether the predictor derived from the objective assessment is involved. These proposed models can be directly used by media industries for video quality estimation, and will ultimately help them to ensure a positive end-user quality of experience on future mobile devices after the adaptation of the latest video encoding technologies.

Incremental and inevitable: Contextualising the Threshold Learning Outcomes for law

This article situates the development of the Threshold Learning Outcomes for law in relation to broader national and international trends in legal education and higher education regulation. It also addresses the significance of recent changes to the Australian higher education regulatory landscape catalysed by the current Government's commitment to reducing regulation and red tape for the sector.

Hybrid constant factor incremental delta modulators

The paper presents a new adaptive delta modulator, called the hybrid constant factor incremental delta modulator (HCFIDM), which uses instantaneous as well as syllabic adaptation of the step size. Three instantaneous algorithms have been used: two new instantaneous algorithms (CFIDM-3 and CFIDM-2) and the third, Song's voice ADM (SVADM). The quantisers have been simulated on a digital computer and their performances studied. The figure of merit used is the SNR with correlated, /?C-shaped Gaussian signals and real speech as the input. The results indicate that the hybrid technique is superior to the nonhybrid adaptive quantisers. Also, the two new instantaneous algorithms developed have improved SNR and fast response to step inputs as compared to the earlier systems.

Algorithm for incremental compaction of geometrical layouts

In this paper, a new incremental algorithm for layout compaction is proposed. In addition to its linear time performance in terms of the number of rectangles in the layout, we also describe how incremental compaction can form a good feature in the design of a layout editor. The design of such an editor is also described. In the design of the editor, we describe how arrays can be used to implement quadtrees that represent VLSI layouts. Such a representation provides speed of data access and low storage requirements.

Constant factor incremental delta modulator

This paper presents a new algorithm for the step-size change of instantaneous adaptive delta modulator. The present strategy is such that the step-size at any sampling instant can increase or decrease by either of the two constant factors or can remain the same, depending upon the combination of three or four most recent output bits. The quantizer has been simulated on a digital computer, and its performance compared with other quantizers. The figure of merit used is the SNR with gaussian signals as the input. The results indicate that the new design can give an improved SNR over a wider dynamic range and fast response to step inputs, as compared to the earlier systems.

Acute and chronic effects of dietary nitrate supplementation on blood pressure and the physiological responses to moderate-intensity and incremental exercise

Dietary nitrate (NO3−) supplementation with beetroot juice (BR) over 4–6 days has been shown to reduce the O2 cost of submaximal exercise and to improve exercise tolerance. However, it is not known whether shorter (or longer) periods of supplementation have similar (or greater) effects. We therefore investigated the effects of acute and chronic NO3− supplementation on resting blood pressure (BP) and the physiological responses to moderate-intensity exercise and ramp incremental cycle exercise in eight healthy subjects. Following baseline tests, the subjects were assigned in a balanced crossover design to receive BR (0.5 l/day; 5.2 mmol of NO3−/day) and placebo (PL; 0.5 l/day low-calorie juice cordial) treatments. The exercise protocol (two moderate-intensity step tests followed by a ramp test) was repeated 2.5 h following first ingestion (0.5 liter) and after 5 and 15 days of BR and PL. Plasma nitrite concentration (baseline: 454 ± 81 nM) was significantly elevated (+39% at 2.5 h postingestion; +25% at 5 days; +46% at 15 days; P < 0.05) and systolic and diastolic BP (baseline: 127 ± 6 and 72 ± 5 mmHg, respectively) were reduced by ∼4% throughout the BR supplementation period (P < 0.05). Compared with PL, the steady-state V̇o2 during moderate exercise was reduced by ∼4% after 2.5 h and remained similarly reduced after 5 and 15 days of BR (P < 0.05). The ramp test peak power and the work rate at the gas exchange threshold (baseline: 322 ± 67 W and 89 ± 15 W, respectively) were elevated after 15 days of BR (331 ± 68 W and 105 ± 28 W; P < 0.05) but not PL (323 ± 68 W and 84 ± 18 W). These results indicate that dietary NO3− supplementation acutely reduces BP and the O2 cost of submaximal exercise and that these effects are maintained for at least 15 days if supplementation is continued.