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.

Omtvedt Innovation Award Presented to Allen G. Blezek

It is such a pleasure to honor innovation and accomplishment in the Institute of Agriculture and Natural Resources today through this 2007 Omtvedt Innovation Award. This award is made possible because of the generosity of Leone and the late Neal Harlan, great friends of the Institute of Agriculture and Natural Resources. The Harlans had the vision and the foresight to realize the importance of recognizing and supporting outstanding and innovative work in the Institute. They honored Irv Omtvedt on his retirement as Vice Chancellor of the Institute with a generous gift of funds to support the Omtvedt Innovation Awards. These awards recognize areas of strength and promise within the Institute, as well as innovative research and programming by our faculty, staff, and students.

The Probe, Issue 174 – March 1997

Outwitting Urban Beaver, by C. E. "Ki" Faulkner, Regional Director, Region 0, NADCA Bear Gets Attention in Southeast Chinese disease Threatens Rabbits Product Announcements: BEAR BE GONE™ -- a device designed to deter bears from foraging in trash cans. Booklet: "Using Guard Animals to Protect Livestock" Abstracts Published at the 3rd Annual Conference of The Wildlife Society: A case study of black bear movements and survival after landfill closure in the central Adirondacks, by Ann M. Russell and S.L. Simek Ecology of coyotes in a sheep ranching environment, by Ben N. Sacks, J.C.C. Neale, M. Jaeger, and D. R. McCullough Design and analysis of carnivore scent-station surveys, by Glen Sargeant, Douglas H. Johnson, and William Berg Public attitudes toward wildlife damage management, by Robert H. Schmidt, M.W. Brunson, andD. Reiter Human dimensions of wildlife contraception, by Robert H. Schmidt and D. E. Mclvor Economic assessment of rabies control efforts in Texas, by Randy M. Smith Methyl salicylate: a naturally occurring avian repellent, by Shirley Wager-Page A brief historical perspective on wildlife contraception research, by Robert J. Warren Wildlife-caused losses to agriculture in 1994, by Alice P. Wywialowski

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).

Bioremediation of PAHs - Limitations and soultions

Introduction 1.1 Occurrence of polycyclic aromatic hydrocarbons (PAH) in the environment Worldwide industrial and agricultural developments have released a large number of natural and synthetic hazardous compounds into the environment due to careless waste disposal, illegal waste dumping and accidental spills. As a result, there are numerous sites in the world that require cleanup of soils and groundwater. Polycyclic aromatic hydrocarbons (PAHs) are one of the major groups of these contaminants (Da Silva et al., 2003). PAHs constitute a diverse class of organic compounds consisting of two or more aromatic rings with various structural configurations (Prabhu and Phale, 2003). Being a derivative of benzene, PAHs are thermodynamically stable. In addition, these chemicals tend to adhere to particle surfaces, such as soils, because of their low water solubility and strong hydrophobicity, and this results in greater persistence under natural conditions. This persistence coupled with their potential carcinogenicity makes PAHs problematic environmental contaminants (Cerniglia, 1992; Sutherland, 1992). PAHs are widely found in high concentrations at many industrial sites, particularly those associated with petroleum, gas production and wood preserving industries (Wilson and Jones, 1993). 1.2 Remediation technologies Conventional techniques used for the remediation of soil polluted with organic contaminants include excavation of the contaminated soil and disposal to a landfill or capping - containment - of the contaminated areas of a site. These methods have some drawbacks. The first method simply moves the contamination elsewhere and may create significant risks in the excavation, handling and transport of hazardous material. Additionally, it is very difficult and increasingly expensive to find new landfill sites for the final disposal of the material. The cap and containment method is only an interim solution since the contamination remains on site, requiring monitoring and maintenance of the isolation barriers long into the future, with all the associated costs and potential liability. A better approach than these traditional methods is to completely destroy the pollutants, if possible, or transform them into harmless substances. Some technologies that have been used are high-temperature incineration and various types of chemical decomposition (for example, base-catalyzed dechlorination, UV oxidation). However, these methods have significant disadvantages, principally their technological complexity, high cost , and the lack of public acceptance. Bioremediation, on the contrast, is a promising option for the complete removal and destruction of contaminants. 1.3 Bioremediation of PAH contaminated soil & groundwater Bioremediation is the use of living organisms, primarily microorganisms, to degrade or detoxify hazardous wastes into harmless substances such as carbon dioxide, water and cell biomass Most PAHs are biodegradable unter natural conditions (Da Silva et al., 2003; Meysami and Baheri, 2003) and bioremediation for cleanup of PAH wastes has been extensively studied at both laboratory and commercial levels- It has been implemented at a number of contaminated sites, including the cleanup of the Exxon Valdez oil spill in Prince William Sound, Alaska in 1989, the Mega Borg spill off the Texas coast in 1990 and the Burgan Oil Field, Kuwait in 1994 (Purwaningsih, 2002). Different strategies for PAH bioremediation, such as in situ , ex situ or on site bioremediation were developed in recent years. In situ bioremediation is a technique that is applied to soil and groundwater at the site without removing the contaminated soil or groundwater, based on the provision of optimum conditions for microbiological contaminant breakdown.. Ex situ bioremediation of PAHs, on the other hand, is a technique applied to soil and groundwater which has been removed from the site via excavation (soil) or pumping (water). Hazardous contaminants are converted in controlled bioreactors into harmless compounds in an efficient manner. 1.4 Bioavailability of PAH in the subsurface Frequently, PAH contamination in the environment is occurs as contaminants that are sorbed onto soilparticles rather than in phase (NAPL, non aqueous phase liquids). It is known that the biodegradation rate of most PAHs sorbed onto soil is far lower than rates measured in solution cultures of microorganisms with pure solid pollutants (Alexander and Scow, 1989; Hamaker, 1972). It is generally believed that only that fraction of PAHs dissolved in the solution can be metabolized by microorganisms in soil. The amount of contaminant that can be readily taken up and degraded by microorganisms is defined as bioavailability (Bosma et al., 1997; Maier, 2000). Two phenomena have been suggested to cause the low bioavailability of PAHs in soil (Danielsson, 2000). The first one is strong adsorption of the contaminants to the soil constituents which then leads to very slow release rates of contaminants to the aqueous phase. Sorption is often well correlated with soil organic matter content (Means, 1980) and significantly reduces biodegradation (Manilal and Alexander, 1991). The second phenomenon is slow mass transfer of pollutants, such as pore diffusion in the soil aggregates or diffusion in the organic matter in the soil. The complex set of these physical, chemical and biological processes is schematically illustrated in Figure 1. As shown in Figure 1, biodegradation processes are taking place in the soil solution while diffusion processes occur in the narrow pores in and between soil aggregates (Danielsson, 2000). Seemingly contradictory studies can be found in the literature that indicate the rate and final extent of metabolism may be either lower or higher for sorbed PAHs by soil than those for pure PAHs (Van Loosdrecht et al., 1990). These contrasting results demonstrate that the bioavailability of organic contaminants sorbed onto soil is far from being well understood. Besides bioavailability, there are several other factors influencing the rate and extent of biodegradation of PAHs in soil including microbial population characteristics, physical and chemical properties of PAHs and environmental factors (temperature, moisture, pH, degree of contamination). Figure 1: Schematic diagram showing possible rate-limiting processes during bioremediation of hydrophobic organic contaminants in a contaminated soil-water system (not to scale) (Danielsson, 2000). 1.5 Increasing the bioavailability of PAH in soil Attempts to improve the biodegradation of PAHs in soil by increasing their bioavailability include the use of surfactants , solvents or solubility enhancers.. However, introduction of synthetic surfactant may result in the addition of one more pollutant. (Wang and Brusseau, 1993).A study conducted by Mulder et al. showed that the introduction of hydropropyl-ß-cyclodextrin (HPCD), a well-known PAH solubility enhancer, significantly increased the solubilization of PAHs although it did not improve the biodegradation rate of PAHs (Mulder et al., 1998), indicating that further research is required in order to develop a feasible and efficient remediation method. Enhancing the extent of PAHs mass transfer from the soil phase to the liquid might prove an efficient and environmentally low-risk alternative way of addressing the problem of slow PAH biodegradation in soil.

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.

Biochemische Charakterisierung der Zyklin-abhängigen Kinase 2,Aktivator-Komplexe des Parasiten Eimeria tenella sowie deren Nutzung in der Wirkstoffforschung

Der Stamm der Apicomplexa ist eine artenreiche Gruppe, der einzellige, meist obligat intrazelluläre Parasiten angehören, darunter auch erstzunehmende Krankheitserreger wie Plasmodium sp. sowie tierpathogene Vertreter wie Eimeria sp. und Theileria sp. Eimeria sp. verursacht die Kokzidiose beim Huhn. Diese Krankheit bedingt weltweite Verluste in der Geflügelindustrie von etwa 3 Milliarden US$ pro Jahr [DALLOUL & LILLEHOJ, 2006; SHIRLEY et al., 2007; LUCIUS & LOOS-FRANK, 2008]. Die Parasiten weisen eine hohe Resistenzbildungsrate gegen vorhandene Wirkstoffe auf. Zudem ist der Einsatz von Vakzinen mit Nebenwirkungen verbunden und für hohe Produktionskosten verantwortlich. Daher ist die Entwicklung von neuen, kostengünstigen und effektiven Kokzidiostatika eine dringend notwendige Herausforderung [KINNAIRD et al., 2004]. rnAuf Grund ihrer essentiellen, regulatorischen Funktion im eukaryotischen Zellzyklus sind Zyklin-abhängige Kinasen (CDKs) validierte Zielproteine [LEHNINGER et al., 2005]. Auch Eimeria tenella CDC2-related kinase 2 (EtCRK2) wurde bereits mittels des bekannten CDK-Inhibitors Flavopiridol als Zielprotein chemisch validiert [ENGELS et al., 2010]. Wie bei allen CDKs ist die Aktivität von EtCRK2 abhängig von der Bindung eines Aktivators, der zur Zyklin-Proteinfamilie gehört. Dieser natürliche EtCRK2-Aktivator war jedoch bislang nicht bekannt. Deshalb war ein Teil dieser Arbeit die Identifizierung des natürlichen EtCRK2-Aktivators. Bioinformatische Analysen identifizierten vier E. tenella Zyklin-ähnliche Proteine (EtCYC1, EtCYC3a, EtCYC3b und EtCYC4), die nah verwandt zu den Plasmodium falciparum-Zyklinen sind [ENGELS et al., 2010; SUÁREZ FERNÁNDEZ et al., bislang unveröffentlichte Daten]. Im Rahmen dieser Arbeit konnten zwei neue Aktivatoren identifiziert und biochemisch charakterisiert werden: der bekannte CDK-Aktivator XlRINGO und das neue E. tenella-Zyklin EtCYC3a. Nachdem der nicht-radioaktive TR-FRET-Assay für die EtCRK2 etabliert und optimiert wurde, konnte die EtCRK2-Aktivität im Komplex mit beiden Aktivatoren und weitere wichtige kinetische Parameter bestimmt werden.rnZusätzlich wurde dieser Assay zum in vitro Screening einer kommerziellen Chemikalienbibliothek auf die EtCRK2 eingesetzt, um potentielle Inhibitoren für EtCRK2 zu identifizieren. Dieses in vitro Screening gefolgt von einer in silico Hit-Anreicherung identifizierte 19 aktive Verbindungen für die durch EtCYC3a und XlRINGO aktivierte EtCRK2. Zudem wurden drei Struktur-Cluster definiert: Naphthoquinone, 8-Hydroxyquinoline und 2-Pyrimidinyl-aminopiperidin-propan-2-ole. rnDie aktivsten Vertreter von jedem Cluster wurden als Leitstrukturen ausgewählt und auf EtCRK2 und HsCDK2 getestet. Aufgrund ihrer inhibierenden Wirkung auf EtCRK2 stellen diese Verbindungen viel versprechende Leitstrukturen für die Entwicklung eines neuen Antikokzidiums dar. Hiermit konnte auch gezeigt werden, dass BES124764, der Vertreter des 2-Pyrimidinyl-aminopiperidin-propan-2-ol-Clusters, in der Lage ist, die EtCRK2 selektiv zu inhibieren. rnDaher wird BES124764 sowie einige Derivate in den Leitstruktur-Optimierungsprozess für die Auffindung eines neuen Arzneimittelkandidaten gegen Kokzidiose eingehen.rn