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

Comparative analysis between a PEM fuel cell and an internal combustion engine driving an electricity generator: Technical, economical and ecological aspects

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

DRIVING AND RESTRICTIVE FACTORS IN THE PROCESS OF KNOWLEDGE CREATION: A COMPARATIVE CASE STUDY IN BRAZILIAN TECHNOLOGY-BASED ENTERPRISES

The article aims to analyze the process of knowledge creation in Brazilian technology-based companies, using as a background the driving and restrictive factors found in this process. As the pillars of discussion, four main modes of knowledge conversion were used, according to the Japanese model: socialization, externalization, combination and internalization. The comparative case method through qualitative research was carried out in nine technology-based enterprises that had been incubated or have recently passed through the stage of incubation (so-called graduated companies) in the Technology Park of Sao Carlos, state of Sao Paulo, Brazil. Among the main results, the combination of knowledge was identified as more conscious and structured in graduated companies, in relation to incubated companies. In contrast, it was noted that incubated companies have an environment with greater opportunities for socialization, internalization and externalization of knowledge.

Reconnection studies under different types of turbulence driving

We study a model of fast magnetic reconnection in the presence of weak turbulence proposed by Lazarian and Vishniac (1999) using three-dimensional direct numerical simulations. The model has been already successfully tested in Kowal et al. (2009) confirming the dependencies of the reconnection speed V-rec on the turbulence injection power P-inj and the injection scale l(inj) expressed by a constraint V-rec similar to P(inj)(1/2)l(inj)(3/4)and no observed dependency on Ohmic resistivity. In Kowal et al. (2009), in order to drive turbulence, we injected velocity fluctuations in Fourier space with frequencies concentrated around k(inj) = 1/l(inj), as described in Alvelius (1999). In this paper, we extend our previous studies by comparing fast magnetic reconnection under different mechanisms of turbulence injection by introducing a new way of turbulence driving. The new method injects velocity or magnetic eddies with a specified amplitude and scale in random locations directly in real space. We provide exact relations between the eddy parameters and turbulent power and injection scale. We performed simulations with new forcing in order to study turbulent power and injection scale dependencies. The results show no discrepancy between models with two different methods of turbulence driving exposing the same scalings in both cases. This is in agreement with the Lazarian and Vishniac (1999) predictions. In addition, we performed a series of models with varying viscosity nu. Although Lazarian and Vishniac (1999) do not provide any prediction for this dependence, we report a weak relation between the reconnection speed with viscosity, V-rec similar to nu(-1/4).

The association between low alcohol use and traffic risk behaviors among Brazilian college students

Although there are a large number of studies focused on binge drinking and traffic risk behaviors (TRB), little is known regarding low levels of alcohol consumption and its association to TRB. The aim of this cross-sectional study is to examine the association of low to moderate alcohol intake pattern and TRB in college students in Brazil. 7037 students from a National representative sample were selected under rigorous inclusion criteria. All study participants voluntarily fulfilled a structured, anonymous, and self-questionnaire regarding alcohol and drug use, social-demographic data, and TRB. Alcohol was assessed according to the average number of alcoholic units consumed on standard occasions over the past 12 months. The associations between alcohol intake and TRB were summarized with odds ratio and their confidence interval obtained from logistic regression. Compared with abstainers students who consumed only one alcohol unit had the risk of being a passenger in a car driven by a drunk driver increased by almost four times, students who reported using five or more units were increased by almost five times the risk of being involved in a car crash. Compared with students who consumed one alcohol unit, the risk of driving under the influence of alcohol increased four times in students using three alcohol units. Age group, use of illicit drugs, employment status, gender, and marital status significantly influenced occurrence of TRB among college students. Our study highlights the potential detrimental effects of low and moderate pattern of alcohol consumption and its relation to riding with an intoxicated driver and other TRB. These data suggest that targeted interventions should be implemented in order to prevent negative consequences due to alcohol use in this population. (C) 2012 Elsevier Inc. All rights reserved,

Genetic and environmental risk factors in congenital heart disease functionally converge in protein networks driving heart development

Congenital heart disease (CHD) occurs in similar to 1% of newborns. CHD arises from many distinct etiologies, ranging from genetic or genomic variation to exposure to teratogens, which elicit diverse cell and molecular responses during cardiac development. To systematically explore the relationships between CHD risk factors and responses, we compiled and integrated comprehensive datasets from studies of CHD in humans and model organisms. We examined two alternative models of potential functional relationships between genes in these datasets: direct convergence, in which CHD risk factors significantly and directly impact the same genes and molecules and functional convergence, in which risk factors significantly impact different molecules that participate in a discrete heart development network. We observed no evidence for direct convergence. In contrast, we show that CHD risk factors functionally converge in protein networks driving the development of specific anatomical structures (e.g., outflow tract, ventricular septum, and atrial septum) that are malformed by CHD. This integrative analysis of CHD risk factors and responses suggests a complex pattern of functional interactions between genomic variation and environmental exposures that modulate critical biological systems during heart development.

Dynamical changes from harmonic vibrations of a limited power supply driving a Duffing oscillator

The harmonic oscillations of a Duffing oscillator driven by a limited power supply are investigated as a function of the alternative strength of the rotor. The semi-trivial and non-trivial solutions are derived. We examine the stability of these solutions and then explore the complex behaviors associated with the bifurcations sequences. Interestingly, a 3D diagram provides a global view of the effects of alternate strength on the appearance of chaos and hyperchaos on the system.

Behavioral driving through on line monitoring and activity-dependent stimulation in weakly electric fish

This work has been supported by Brazilian agencies FAPESP, CNPq, CAPES and grants MICINN BFU200908473 and TIN 201019607, SpanishBrazilian Cooperation PHB20070008 and 7ª Convocatoria De PROYECTOS de COOPERACION INTERUNIVERSITARIAUAMSANTANDER con America Latina

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Consensus statement of the European Heart Rhythm Association: updated recommendations for driving by patients with implantable cardioverter defibrillators

Patients with an implantable cardioverter defibrillator (ICD) have an ongoing risk of sudden incapacitation that might cause harm to others while driving a car. Driving restrictions vary across different countries in Europe. The most recent recommendations for driving of ICD patients in Europe were published in 1997 and focused mainly on patients implanted for secondary prevention. In recent years there has been a vast increase in the number of patients with an ICD and in the percentage of patients implanted for primary prevention. The EHRA task force on ICD and driving was formed to reassess the risk of driving for ICD patients based on the literature available. The recommendations are summarized in the following table and are further explained in the document, (Table see text). Driving restrictions are perceived as difficult for patients and their families, and have an immediate consequence for their lifestyle. To increase the adherence to the driving restrictions, adequate discharge of education and follow-up of patients and family are pivotal. The task force members hope this document may serve as an instrument for European and national regulatory authorities to formulate uniform driving regulations.

Cognition and driving in older persons

In Switzerland, approximately 350,000 people aged 70 years or older own a valid driving license. By law, these drivers are medically assessed every other year, most commonly by their general practitioner, to exclude that a medical condition is interfering with their driving skills. A prerequisite for driving is the integration of high-level cognitive functions with perception and motor function. Ageing, per se, does not necessarily impair driving or increase the crash risk. However, medical conditions, such as cognitive impairment and dementia, become more prevalent with advancing age and may contribute to poor driving and an increased crash risk. The extent to which driving skills are impaired depends on the cause of dementia, disease severity, other co-morbidities and individual compensation strategies. Dementia often remains undiagnosed and therefore general practitioners (GPs) can find themselves in the difficult situation to disclose a suspicion about cognitive impairment and queries about medical fitness to drive, at the same time. In addition, the literature suggests that cognitive screening tests, most commonly used by GPs, have a limited role in judging whether an older person remains fit to drive. Further specialist assessment, for example in a memory clinic or on the road testing (ORT), may be helpful when the diagnosis or its implication for driving remain unclear. Here, we review the literature about cognition and driving, for GPs who advise older drivers who wish to continue driving.