Knowledge representation system for assembly using robots

Assembly robots combine the benefits of speed and accuracy with the capability of adaptation to changes in the work environment. However, an impediment to the use of robots is the complexity of the man-machine interface. This interface can be improved by providing a means of using a priori-knowledge and reasoning capabilities for controlling and monitoring the tasks performed by robots. Robots ought to be able to perform complex assembly tasks with the help of only supervisory guidance from human operators. For such supervisory quidance, it is important to express the commands in terms of the effects desired, rather than in terms of the motion the robot must undertake in order to achieve these effects. A suitable knowledge representation can facilitate the conversion of task level descriptions into explicit instructions to the robot. Such a system would use symbolic relationships describing the a priori information about the robot, its environment, and the tasks specified by the operator to generate the commands for the robot

Different approaches to community detection

A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark networks with a particular form of community structure and classified them based on the mathematical techniques they employ. However, this comparison can be misleading because apparent similarities in their mathematical machinery can disguise different reasons for why we would want to employ community detection in the first place. Here we provide a focused review of these different motivations that underpin community detection. This problem-driven classification is useful in applied network science, where it is important to select an appropriate algorithm for the given purpose. Moreover, highlighting the different approaches to community detection also delineates the many lines of research and points out open directions and avenues for future research.Comment: 14 pages, 2 figures. Written as a chapter for forthcoming Advances in network clustering and blockmodeling, and based on an extended version of The many facets of community detection in complex networks, Appl. Netw. Sci. 2: 4 (2017) by the same author

Tracking 3-D body motion for docking and robot control

An advanced method of tracking three-dimensional motion of bodies has been developed. This system has the potential to dynamically characterize machine and other structural motion, even in the presence of structural flexibility, thus facilitating closed loop structural motion control. The system's operation is based on the concept that the intersection of three planes defines a point. Three rotating planes of laser light, fixed and moving photovoltaic diode targets, and a pipe-lined architecture of analog and digital electronics are used to locate multiple targets whose number is only limited by available computer memory. Data collection rates are a function of the laser scan rotation speed and are currently selectable up to 480 Hz. The tested performance on a preliminary prototype designed for 0.1 in accuracy (for tracking human motion) at a 480 Hz data rate includes a worst case resolution of 0.8 mm (0.03 inches), a repeatability of plus or minus 0.635 mm (plus or minus 0.025 inches), and an absolute accuracy of plus or minus 2.0 mm (plus or minus 0.08 inches) within an eight cubic meter volume with all results applicable at the 95 percent level of confidence along each coordinate region. The full six degrees of freedom of a body can be computed by attaching three or more target detectors to the body of interest

Decreased beta-cell mass in diabetes: significance, mechanisms and therapeutic implications

Increasing evidence indicates that decreased functional beta-cell mass is the hallmark of both Type 1 and Type 2 diabetes. This underlies the absolute or relative insulin insufficiency in both conditions. In this For Debate, we consider the possible mechanisms responsible for beta-cell death and impaired function and their relative contribution to insulin insufficiency in diabetes. Beta-cell apoptosis and impaired proliferation consequent to hyperglycaemia is one pathway that could be operating in all forms of diabetes. Autoimmunity and other routes to beta-cell death are also considered. Recognition of decreased functional beta-cell mass and its overlapping multifactorial aetiology in diabetic states, leads us to propose a unifying classification of diabete

Study of effect of arbuscular mycorrhiza (Glomus intraradices) fungus on wheat under nickel stress

ArticleIn many regions of the world soils are contaminated with heavy metals and therefore restricted in their use. For instance, the absorption of nickel (Ni) in the tissue of plants increase the plant’s metabolism and cause physiological disorders or even death. Arbuscular mycorrhizal fungi are known to enhance the tolerance of host plants to abiotic and biotic stress. Thus, we investigated the potential of the arbuscular m ycorrhizal fungi Glomus intraradices to mitigate deleterious effects of Ni in wheat. The experiment was conducted using four levels of Ni (0, 60, 120 and 180 mg per kg of soil) and two levels of mycorrhizal fungi application (with and without Glomus intrar adices ). Nickel stress significantly decreased seed number per spike, thousand - seed weight, seed yield per plant, concentration of chlorophyll a and b. At the same time, we found increased catalase (CAT) enzyme activity and dityrosine (DT) treatments. Mycorrhizal fungi application attenuated Ni effects, i.e. fungal presence increased seed number per spike, thousand - seed weight, chlorophyll a and b. Furthermore mycorrhizal fungi application reduce CAT enzyme activity and DT. In general, our results sugge st that mycorrhizal fungi application reduces harmful effects of Ni stress in wheat

Discovery of new TeV supernova remnant shells in the Galactic plane with H.E.S.S

Supernova remnants (SNRs) are prime candidates for efficient particle acceleration up to the knee in the cosmic ray particle spectrum. In this work we present a new method for a systematic search for new TeV-emitting SNR shells in 2864 hours of H.E.S.S. phase I data used for the H.E.S.S. Galactic Plane Survey. This new method, which correctly identifies the known shell morphologies of the TeV SNRs covered by the survey, HESS J1731-347, RX 1713.7-3946, RCW 86, and Vela Junior, reveals also the existence of three new SNR candidates. All three candidates were extensively studied regarding their morphological, spectral, and multi-wavelength (MWL) properties. HESS J1534-571 was associated with the radio SNR candidate G323.7-1.0, and thus is classified as an SNR. HESS J1912+101 and HESS J1614-518, on the other hand, do not have radio or X-ray counterparts that would permit to identify them firmly as SNRs, and therefore they remain SNR candidates, discovered first at TeV energies as such. Further MWL follow up observations are needed to confirm that these newly discovered SNR candidates are indeed SNRs