ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Niobium Effects on the Recrystallization Behavior on a Full Austenitic 15Cr-15Ni Stainless Steel Investigated Using Adaptive Neural Networks (ANN)

A new series of austenitic stainless steels-Nb stabilized, without Mo additions, non-susceptible to delta ferrite formation and devoid of intemetallic phases (sigma and chi), without deformation induced martensite is being developed, aiming at high temperature applications as well as for corrosive environments. The base steel composition is a 15Cr-15Ni with normal additions of Nb of 0.5, 1.0 and 2 wt%. Mechanical properties, oxidation and corrosion resistance already have been invetigated in previous papers. In this paper, the effects of Nb on the SFE, strain hardening and recrystallization resistance are evaluated with the help of Adaptive Neural Networks (ANN).

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Eine siyāḥa als Bildungsroman? Überlegungen zur Organisation des Reisetextes von Ḥannā Diyāb (1763/64)

Ḥannā Diyābs siyāḥa umfasst Reiseerfahrungen eines jungen Maroniten aus Aleppo, der den französischen Gesandten Paul Lucas im Jahre 1707 auf seiner Rückkehr an den französischen Hof begleitet, eine Zeit lang in Paris bleibt und allein zurückkehrt. Die Hinreise führt über den Libanon, Zypern, Nordafrika und Italien, die Rückkehr nach einer Schiffsreise über das Mittelmeer durch Kleinasien. Der Text versammelt viele Topoi, die aus anderen arabischen Reisetexten bekannt sind: Seesturm, Schiffbruch und Piraten, zerstörte Gebäude und wunderschöne Gärten. Ebenso enthält er Anekdoten, Legenden und Episoden, die vermutlich zum Staunen anregen sollen sowie Frömmigkeit und Tugenden vermitteln. Das Besondere an dem Text liegt in der Kraft des Erzählens, mit der unterschiedliche Textteile – informative, dokumentarische wie unterhaltsame Abschnitte – zu einer zusammenhängenden Reiseerzählung verwoben werden. Die offensichtliche Einschreibung in eine bestimmte, meist als faktual verstandene Textsorte (riḥla, safra oder siyāḥa) und der Authentizitätsanspruch des Erzählers werden mit einer Neigung zur Fiktionalität kombiniert, die sich besonders in der Hervorhebung einzigartiger (Selbst-)Erlebnisse äußert. In dem Vortrag sollen die verschiedenen Facetten von Diyābs siyāḥa als erste Ergebnisse eines close reading des Textes präsentiert werden. Es wird dabei der Arbeitshypothese des Dissertationsprojekts nachgegangen: Die siyāḥa lässt sich als eine Kompilation verschiedener Textsorten, Themen und Schreibweisen interpretieren und liefert daher einen Zugang zu Wissenshorizonten und Wissensordnungen im Aleppo des 18. Jahrhunderts. Ziel ist es allerdings auch, das Funktionieren und den Zweck dieses Textes als individuelles literarisches Ereignis zu bestimmen. In diesem Sinne soll schließlich diskutiert werden, in welcher Hinsicht diese siyāḥa als Bildungsroman verstanden werden kann.