Developing a framework for mapping industrial emergence

The industrial landscape is becoming increasingly complex and dynamic, with innovative technologies stimulating the emergence of new industries and business models. This paper presents a preliminary framework for mapping industrial emergence, based on roadmapping principles, in order to understand the nature and characteristics of such phenomena. The focus at this stage is on historical examples of industrial emergence, with the preliminary framework based on observations from 20 'quick scan' maps, one of which is used to illustrate the framework. The learning from these historical cases, combined with further industrial consultation and literature review, will be used to develop practical methods for strategy and policy application. The paper concludes by summarising key learning points and further work needed to achieve these outcomes. © 2009 PICMET.

Measuring stiffness during arm movements in various dynamic environments

The technique presented in this paper enables a simple, accurate and unbiased measurement of hand stiffness during human arm movements. Using a computer-controlled mechanical interface, the hand is shifted relative to a prediction of the undisturbed trajectory. Stiffness is then computed as the restoring force divided by the position amplitude of the perturbation. A precise prediction algorithm insures the measurement quality. We used this technique to measure stiffness in free movements and after adaptation to a linear velocity dependent force field. The subjects compensated for the external force by co-contracting muscles selectively. The stiffness geometry changed with learning and stiffness tended to increase in the direction of the external force.

Optimization of nanotube electrode geometry in a liquid crystal media from wavefront aberrations

This paper presents experimental optimization of number and geometry of nanotube electrodes in a liquid crystal media from wavefront aberrations for realizing nanophotonic devices. The refractive-index gradient profiles from different nanotube geometries-arrays of one, three, four, and five-were studied along with wavefront aberrations using Zernike polynomials. The optimizations help the device to make application in the areas of voltage reconfigurable microlens arrays, high-resolution displays, wavefront sensors, holograms, and phase modulators. © 2012 Optical Society of America.

EARLY FLOWERING4 recruitment of EARLY FLOWERING3 in the nucleus sustains the Arabidopsis circadian clock

The plant circadian clock is proposed to be a network of several interconnected feedback loops, and loss of any component leads to changes in oscillator speed. We previously reported that Arabidopsis thaliana EARLY FLOWERING4 (ELF4) is required to sustain this oscillator and that the elf4 mutant is arrhythmic. This phenotype is shared with both elf3 and lux. Here, we show that overexpression of either ELF3 or LUX ARRHYTHMO (LUX) complements the elf4 mutant phenotype. Furthermore, ELF4 causes ELF3 to form foci in the nucleus. We used expression data to direct a mathematical position of ELF3 in the clock network. This revealed direct effects on the morning clock gene PRR9, and we determined association of ELF3 to a conserved region of the PRR9 promoter. A cis-element in this region was suggestive of ELF3 recruitment by the transcription factor LUX, consistent with both ELF3 and LUX acting genetically downstream of ELF4. Taken together, using integrated approaches, we identified ELF4/ELF3 together with LUX to be pivotal for sustenance of plant circadian rhythms. © 2012 American Society of Plant Biologists.

Enhancement of Construction Equipment Detection in Video Frames by Combining with Tracking

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.