Motion

This article is about orientation in the conceptual construction and exploration of the world. Orientations that fail to include a satisfactory definition of self as a vital component in ideas of explanation, compulsively leaning towards excessive analytical description(partism)) and resulting in increased numbers of empirically found exceptions to theoretical ideas, also fail to include adequate notions of motion and change. In the science of cognition a three part picture usually results, rather than a two component one in which the extraneous component functions as a compensation from the initial vagueness in ideas. Though this can seem to be a reasonable approach, to proceed from vagueness, to conjecture, empirical test/comparison, a false order in all components of a final theory will continuously result, and ultimately, in one to one correspondence, equate with a separate topic and not with the original. A compulsive and strict adherence to common sense, though not seeming to supply adequate explanation and strained for lingual description/expression, is the only possible route to adequate explanation. In cognition, the perennial stumbling is always at the division between the ethereal and the tangible. It is such an inhibitory obstacle, that in the construction of ideas, language falters to result in the continual construction of new words to “describe” rather than to connect. Though I believe “describe” is also the real ultimate goal, a real connection is never established

Turning marketing promises into business value: The experience of an industrial SME

The article studies the value that businesses should have for their customers and shareholders. It explains how to develop such value to meet or exceed customer's expectations through the application of the promise framework. The promise model includes promises made to customers, promises kept, and promises that involve a synchronized effort from the whole firm to create and deliver value to customers

Nuclear processes associated with plant immunity and pathogen susceptibility

Plants are sessile organisms that have evolved exquisite and sophisticated mechanisms to adapt to their biotic and abiotic environment. Plants deploy receptors and vast signalling networks to detect, transmit and respond to a given biotic threat by inducing properly dosed defence responses. Genetic analyses and, more recently, next-generation -omics approaches have allowed unprecedented insights into the mechanisms that drive immunity. Similarly, functional genomics and the emergence of pathogen genomes have allowed reciprocal studies on the mechanisms governing pathogen virulence and host susceptibility, collectively allowing more comprehensive views on the processes that govern disease and resistance. Among others, the identification of secreted pathogen molecules (effectors) that modify immunity-associated processes has changed the plant–microbe interactions conceptual landscape. Effectors are now considered both important factors facilitating disease and novel probes, suited to study immunity in plants. In this review, we will describe the various mechanisms and processes that take place in the nucleus and help regulate immune responses in plants. Based on the premise that any process required for immunity could be targeted by pathogen effectors, we highlight and describe a number of functional assays that should help determine effector functions and their impact on immune-related processes. The identification of new effector functions that modify nuclear processes will help dissect nuclear signalling further and assist us in our bid to bolster immunity in crop plants

Seeing motion and apparent motion

In apparent motion experiments, participants are presented with what is in fact a succession of two brief stationary stimuli at two different locations, but they report an impression of movement. Philosophers have recently debated whether apparent motion provides evidence in favour of a particular account of the nature of temporal experience. I argue that the existing discussion in this area is premised on a mistaken view of the phenomenology of apparent motion and, as a result, the space of possible philosophical positions has not yet been fully explored. In particular, I argue that the existence of apparent motion is compatible with an account of the nature of temporal experience that involves a version of direct realism. In doing so, I also argue against two other claims often made about apparent motion, viz. that apparent motion is the psychological phenomenon that underlies motion experience in the cinema, and that apparent motion is subjectively indistinguishable from real motion

An Extensible Benchmarking Infrastructure for Motion Planning Algorithms

Sampling-based planning algorithms are the most common probabilistically complete algorithms and are widely used on many robot platforms. Within this class of algorithms, many variants have been proposed over the last 20 years, yet there is still no characterization of which algorithms are well-suited for which classes of problems. This has motivated us to develop a benchmarking infrastructure for motion planning algorithms. It consists of three main components. First, we have created an extensive benchmarking software framework that is included with the Open Motion Planning Library (OMPL), a C++ library that contains implementations of many sampling-based algorithms. Second, we have defined extensible formats for storing benchmark results. The formats are fairly straightforward so that other planning libraries could easily produce compatible output. Finally, we have created an interactive, versatile visualization tool for compact presentation of collected benchmark data. The tool and underlying database facilitate the analysis of performance across benchmark problems and planners.Comment: Submitted to IEEE Robotics & Automation Magazine (Special Issue on Replicable and Measurable Robotics Research), 201

Integrated region- and pixel-based approach to background modelling

In this paper a new probabilistic method for background modelling is proposed, aimed at the application in video surveillance tasks using a monitoring static camera. Recently, methods employing Time-Adaptive, Per Pixel, Mixture of Gaussians (TAPPMOG) modelling have become popular due to their intrinsic appealing properties. Nevertheless, they are not able per se to monitor global changes in the scene, because they model the background as a set of independent pixel processes. In this paper, we propose to integrate this kind of pixel-based information with higher level region-based information, that permits to manage also sudden changes of the background. These pixel- and regionbased modules are naturally and effectively embedded in a probabilistic Bayesian framework called particle filtering, that allows a multi-object tracking. Experimental comparison with a classic pixel-based approach reveals that the proposed method is really effective in recovering from situations of sudden global illumination changes of the background, as well as limited non-uniform changes of the scene illumination.

Dual motion valve with single motion input

A dual motion valve includes two dual motion valve assemblies with a rotary input which allows the benefits of applying both rotary and axial motion to a rotary sealing element with a plurality of ports. The motion of the rotary sealing element during actuation provides axial engagement of the rotary sealing element with a stationary valve plate which also has ports. Fluid passages are created through the valve when the ports of the rotary sealing element are aligned with the ports of the stationary valve plate. Alignment is achieved through rotation of the rotary sealing element with respect to the stationary valve plate. The fluid passages provide direct paths which minimize fluid turbulence created in the fluid as it passes through the valve

Event-Based Motion Segmentation by Motion Compensation

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution. Since events are caused by the apparent motion of objects, event-based cameras sample visual information based on the scene dynamics and are, therefore, a more natural fit than traditional cameras to acquire motion, especially at high speeds, where traditional cameras suffer from motion blur. However, distinguishing between events caused by different moving objects and by the camera's ego-motion is a challenging task. We present the first per-event segmentation method for splitting a scene into independently moving objects. Our method jointly estimates the event-object associations (i.e., segmentation) and the motion parameters of the objects (or the background) by maximization of an objective function, which builds upon recent results on event-based motion-compensation. We provide a thorough evaluation of our method on a public dataset, outperforming the state-of-the-art by as much as 10%. We also show the first quantitative evaluation of a segmentation algorithm for event cameras, yielding around 90% accuracy at 4 pixels relative displacement.Comment: When viewed in Acrobat Reader, several of the figures animate. Video: https://youtu.be/0q6ap_OSBA