Search results for "Mach"
showing 10 items of 3360 documents
Hard material small-batch industrial machining robot
2018
Abstract Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the developme…
Me, My Bot and His Other (Robot) Woman? Keeping Your Robot Satisfied in the Age of Artificial Emotion
2018
With a backdrop of action and science fiction movie horrors of the dystopian relationship between humans and robots, surprisingly to date-with the exception of ethical discussions-the relationship aspect of humans and sex robots has seemed relatively unproblematic. The attraction to sex robots perhaps is the promise of unproblematic affectionate and sexual interactions, without the need to consider the other&rsquo
An Artificial Bee Colony Approach for Classification of Remote Sensing Imagery
2018
This paper presents a novel Artificial Bee Colony (ABC) approach for supervised classification of remote sensing images. One proposes to apply an ABC algorithm to optimize the coefficients of the set of polynomial discriminant functions. We have experimented the proposed ABC-based classifier algorithm for a Landsat 7 ETM+ image database, evaluating the influence of the ABC model parameters on the classifier performances. Such ABC model parameters are: numbers of employed/onlooker/scout bees, number of epochs, and polynomial degree. One has compared the best ABC classifier Overall Accuracy (OA) with the performances obtained using a set of benchmark classifiers (NN, NP, RBF, and SVM). The re…
PolyACO+: a multi-level polygon-based ant colony optimisation classifier
2017
Ant Colony Optimisation for classification has mostly been limited to rule based approaches where artificial ants walk on datasets in order to extract rules from the trends in the data, and hybrid approaches which attempt to boost the performance of existing classifiers through guided feature reductions or parameter optimisations. A recent notable example that is distinct from the mainstream approaches is PolyACO, which is a proof of concept polygon-based classifier that resorts to ant colony optimisation as a technique to create multi-edged polygons as class separators. Despite possessing some promise, PolyACO has some significant limitations, most notably, the fact of supporting classific…
A Novel Border Identification Algorithm Based on an “Anti-Bayesian” Paradigm
2013
Published version of a chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_23 Border Identification (BI) algorithms, a subset of Prototype Reduction Schemes (PRS) aim to reduce the number of training vectors so that the reduced set (the border set) contains only those patterns which lie near the border of the classes, and have sufficient information to perform a meaningful classification. However, one can see that the true border patterns (“near” border) are not able to perform the task independently as they are not able to always distinguish the testing samples. Thus, researchers have worked on thi…
Variable neighborhood descent for the incremental graph drawing
2017
Abstract Graphs are used to represent reality in several areas of knowledge. Drawings of graphs have many applications, from project scheduling to software diagrams. The main quality desired for drawings of graphs is readability, and crossing reduction is a fundamental aesthetic criterion for a good representation of a graph. In this paper we target the edge crossing reduction in the context of incremental graph drawing, in which we want to preserve the layout of a graph over successive drawings. We propose a hybrid method based on the GRASP (Greedy Randomized Adaptive Search Procedure) and VND (Variable Neighborhood Descent) methodologies and compare it with previous methods via simulation.
On Detection of Network-Based Co-residence Verification Attacks in SDN-Driven Clouds
2017
Modern cloud environments allow users to consume computational and storage resources in the form of virtual machines. Even though machines running on the same cloud server are logically isolated from each other, a malicious customer can create various side channels to obtain sensitive information from co-located machines. In this study, we concentrate on timely detection of intentional co-residence attempts in cloud environments that utilize software-defined networking. SDN enables global visibility of the network state which allows the cloud provider to monitor and extract necessary information from each flow in every virtual network in online mode. We analyze the extracted statistics on d…
Kick Detection and Influx Size Estimation during Offshore Drilling Operations using Deep Learning
2019
An uncontrolled or unobserved influx or kick during drilling has the potential to induce a well blowout, one of the most harmful incidences during drilling both in regards to economic and environmental cost. Since kicks during drilling are serious risks, it is important to improve kick and loss detection performance and capabilities and to develop automatic flux detection methodology. There are clear patterns during a influx incident. However, due to complex processes and sparse instrumentation it is difficult to predict the behaviour of kicks or losses based on sensor data combined with physical models alone. Emerging technologies within Deep Learning are however quite adapt at picking up …
Intelligence artificielle : quel avenir en anatomie pathologique ?
2019
Resume Les techniques d’intelligence artificielle et en particulier les reseaux de neurones profonds (Deep Learning) sont en pleine emergence dans le domaine biomedical. Les reseaux de neurones s’inspirent du modele biologique, ils sont interconnectes entre eux et suivent des modeles mathematiques. Lors de l’utilisation des reseaux de neurones artificiels, deux phases sont necessaires : une phase d’apprentissage et une phase d’exploitation. Les deux principales applications sont la classification et la regression. Des outils informatiques comme les processeurs graphiques accelerateurs de calcul ou des bibliotheques de developpement specifiques ont donne un nouveau souffle a ces techniques. …
Effect of various dentin disinfection protocols on the bond strength of resin modified glass ionomer restorative material.
2017
Background Disinfection of dentin surface prior to any restorative therapy is important for the longevity of the treatment rendered. However, these dentin disinfection methods should itself not interfere with the adhesion of the restorative material. Therefore the aim of this study was to determine the effect of various dentin disinfection protocols on the shear bond strength (SBS) of resin modified glass ionomer cement (RMGIC). Material and methods The occlusal surface of 40 extracted premolars were trimmed to obtain a flat dentinal surface and was randomly divided into four groups. CTRL was the control group; NaOCl was 1% sodium hypochlorite disinfection group; CHX was 2% chlorhexidine di…