JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, 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 pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical 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 patterns in which reasonably accurate results were obtained.

Problem of assignment cells to switches in a cellular mobile network via beam search method

The problem of assigning cells to switches in a cellular mobile network is an NP-hard optimization problem. So, real size mobile networks could not be solved by using exact methods. The alternative is the use of the heuristic methods, because they allow us to find a good quality solution in a quite satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach to provide good solutions for medium- and large-sized cellular mobile network.

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.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, 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 pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation 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 patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Analysis of rocuronium in human plasma by liquid chromatography-tandem mass spectrometry with application in clinical pharmacokinetics

Rocuronium (ROC) is a neuromuscular blocking agent used in surgical procedures which is eliminated primarily by biliary excretion. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for analysis of ROC in human plasma. Separation of ROC and IS (verapamil) was performed using an endcapped C-18 column and a mixture of water:acetonitrile:trifluoracetic acid (50:50:0.1, v/v) as mobile phase. Aliquots of 100 mu L of human plasma were extracted at pH 3, using dichloromethane. The lower limit of quantification of 5 ng/mL shows the high sensitivity of this method. Intra- and inter-assay precision (as relative standard deviation) was all <= 14.2% and accuracy (as relative standard error) did not exceed 10.1%. The validated method was successfully applied to quantify ROC concentrations in patients under surgical procedures up to 6 h after the administration of the 0.4-0.9 mg/kg ROC. The pharmacokinetic parameter estimations of ROC showed AUC/dose of 563 mu g min/mL, total clearance of 2.5 mL/min/kg, volume of distribution at steady state of 190 mL/kg and mean residence time of 83 min. (C) 2013 Elsevier B.V. All rights reserved.

Think: guia de desenvolvimento mobile ágil em equipes reduzidas

Currently, applications for smartphones and tablets, called apps, are becoming increasingly relevant and attract more attention from users and finally the developers. With the Application Stores, services provided by the company that maintains the platform, access to such applications is as or more simplified than to web sites, with the advantage of anenhanced user experience and focused on the mobile device, and enjoy natives resources as camera, audio, storage, integration with other applications, etc. They present a great opportunity for independent developers, who can now develop an application and make it availabl e to all users of that platform, at free or at a cost that is usually low. Even students may create their applications in the intervals of their classes and sell them in stores. Making use of tools and services, free or at low cost, anyone can develop quality applications, that can be marketed and have a large number of users even in adverse situations in which the application is not the focus of developer productivity. However, such to ols do not seem to be well used, or are unknown, or its purpose is not considered important, and this paper tries to show the real importance of these tools in the rapid development of quality software. This project presents several tools, services and practices, which together make it possible to develop an application for various mobile platforms, independently and with a team of a few people, as demonstrated. However, this paper aims not to say that the development of software today it is easy and simple, but there are currently a large set of tools, for various platforms, that assists and enhances the work of the programmer

Rapid and sensitive ultra-high-pressure liquid chromatography method for quantification of antichagasic benznidazole in plasma: application in a preclinical pharmacokinetic study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ethyl tert-Butyl Ether and Methyl tert-Butyl Ether: Status, Review, and Alternative Use Exploring the Environmental Issues of Mobile, Recalcitrant

Petroleum products leaking from under ground storage tanks have raised concerns regarding the quality of ground water resources, The concerns about the environmental behavior and rate of MTBE as an oxygenated additive prompted this iuvestigation to explore the technical characteristics of MTBE in comparison to ETBF. Evaluation of the existing literature suggests that ETBE has more favorable characteristics than MTBE. Findings in this research suggest that ETBE is a technically sound oxygenated octane enhancer, which can help refiners meet specificatios for cleaner burning gasoline.

Simultaneous determination of dextromethorphan, dextrorphan and doxylamine in human plasma by HPLC coupled to electrospray ionization tandem mass spectrometry: Application to a pharmacokinetic study

In the present study, a fast, sensitive and robust method to quantify dextromethorphan, dextrorphan and doxylamine in human plasma using deuterated internal standards (IS) is described. The analytes and the IS were extracted from plasma by a liquid-liquid extraction (LLE) using diethyl-ether/hexane (80/20, v/v). Extracted samples were analyzed by high performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Chromatographic separation was performed by pumping the mobile phase (acetonitrile/water/formic acid (90/9/1, v/v/v) during 4.0 min at a flow-rate of 1.5 mL min(-1) into a Phenomenex Gemini (R) C18, 5 mu m analytical column (150 x 4.6 mm id.). The calibration curve was linear over the range from 0.2 to 200 ng mL(-1) for dextromethorphan and doxylamine and 0.05 to 10 ng mL(-1) for dextrorphan. The intra-batch precision and accuracy (%CV) of the method ranged from 2.5 to 9.5%, and 88.9 to 105.1%, respectively. Method inter-batch precision (%CV) and accuracy ranged from 6.7 to 10.3%, and 92.2 to 107.1%, respectively. The run-time was for 4 min. The analytical procedure herein described was used to assess the pharmacokinetics of dextromethorphan, dextrorphan and doxylamine in healthy volunteers after a single oral dose of a formulation containing 30 mg of dextromethorphan hydrobromide and 12.5 mg of doxylamine succinate. The method has high sensitivity, specificity and allows high throughput analysis required for a pharmacokinetic study. (C) 2012 Elsevier B.V. All rights reserved.

AN EFFICIENT HPLC-UV METHOD FOR THE QUANTITATIVE DETERMINATION OF CEFADROXIL IN HUMAN PLASMA AND ITS APPLICATION IN PHARMACOKINETIC STUDIES

Cefadroxil is a semi-synthetic first-generation oral cephalosporin used in the treatment of mild to moderate infections of the respiratory and urinary tracts, skin and soft tissue infections. In this work a simple, rapid, economic and sensitive HPLC-UV method is described for the quantitative determination of cefadroxil in human plasma samples using lamivudine as internal standard. Sample pre-treatment was accomplished through protein precipitation with acetonitrile and chromatographic separation was performed with a mobile phase consisting of a mixture of sodium dihydrogen phosphate monohydrate solution, methanol and acetonitrile in the ratio of 90:8:2 (v/v/v) at a flow rate of 1.0mL/min. The proposed method is linear between 0.4 to 40.0 mu g/mL and its average recovery is 102.21% for cefadroxil and 97.94% for lamivudine. The method is simple, sensitive, reproducible, less time consuming for determination of cefadroxil in human plasma. The method can therefore be recommended for pharmacokinetics studies, including bioavailability and bioequivalence studies.

Chiral HPLC analysis of donepezil, 5-O-desmethyl donepezil and 6-O-desmethyl donepezil in culture medium: application to fungal biotransformation studies

An high performance liquid chromatography (HPLC) method for the enantioselective determination of donepezil (DPZ), 5-O-desmethyl donepezil (5-ODD), and 6-O-desmethyl donepezil (6-ODD) in Czapek culture medium to be applied to biotransformation studies with fungi is described for the first time. The HPLC analysis was carried out using a Chiralpak AD-H column with hexane/ethanol/methanol (75:20:5, v/v/v) plus 0.3 % triethylamine as mobile phase and UV detection at 270 nm. Sample preparation was carried out by liquid-liquid extraction using ethyl acetate as extractor solvent. The method was linear over the concentration range of 100-10,000 ng mL(-1) for each enantiomer of DPZ (r a parts per thousand yenaEuro parts per thousand 0.9985) and of 100-5,000 ng mL(-1) for each enantiomer of 5-ODD (r a parts per thousand yenaEuro parts per thousand 0.9977) and 6-ODD (r a parts per thousand yenaEuro parts per thousand 0.9951). Within-day and between-day precision and accuracy evaluated by relative standard deviations and relative errors, respectively, were lower than 15 % for all analytes. The validated method was used to assess DPZ biotransformation by the fungi Beauveria bassiana American Type Culture Collection (ATCC) 7159 and Cunninghamella elegans ATCC 10028B. Using the fungus B. bassiana ATCC 7159, a predominant formation of (R)-5-ODD was observed while for the fungus C. elegans ATCC 10028B, DPZ was biotransformed to (R)-6-ODD with an enantiomeric excess of 100 %.

Dynamic services in mobile ad hoc networks

The increasing diffusion of wireless-enabled portable devices is pushing toward the design of novel service scenarios, promoting temporary and opportunistic interactions in infrastructure-less environments. Mobile Ad Hoc Networks (MANET) are the general model of these higly dynamic networks that can be specialized, depending on application cases, in more specific and refined models such as Vehicular Ad Hoc Networks and Wireless Sensor Networks. Two interesting deployment cases are of increasing relevance: resource diffusion among users equipped with portable devices, such as laptops, smart phones or PDAs in crowded areas (termed dense MANET) and dissemination/indexing of monitoring information collected in Vehicular Sensor Networks. The extreme dynamicity of these scenarios calls for novel distributed protocols and services facilitating application development. To this aim we have designed middleware solutions supporting these challenging tasks. REDMAN manages, retrieves, and disseminates replicas of software resources in dense MANET; it implements novel lightweight protocols to maintain a desired replication degree despite participants mobility, and efficiently perform resource retrieval. REDMAN exploits the high-density assumption to achieve scalability and limited network overhead. Sensed data gathering and distributed indexing in Vehicular Networks raise similar issues: we propose a specific middleware support, called MobEyes, exploiting node mobility to opportunistically diffuse data summaries among neighbor vehicles. MobEyes creates a low-cost opportunistic distributed index to query the distributed storage and to determine the location of needed information. Extensive validation and testing of REDMAN and MobEyes prove the effectiveness of our original solutions in limiting communication overhead while maintaining the required accuracy of replication degree and indexing completeness, and demonstrates the feasibility of the middleware approach.