Control and Guidance of Low-Cost Robots via Gesture Perception for Monitoring Activities in the Home

This paper describes the development of a low-cost mini-robot that is controlled by visual gestures. The prototype allows a person with disabilities to perform visual inspections indoors and in domestic spaces. Such a device could be used as the operator's eyes obviating the need for him to move about. The robot is equipped with a motorised webcam that is also controlled by visual gestures. This camera is used to monitor tasks in the home using the mini-robot while the operator remains quiet and motionless. The prototype was evaluated through several experiments testing the ability to use the mini-robot’s kinematics and communication systems to make it follow certain paths. The mini-robot can be programmed with specific orders and can be tele-operated by means of 3D hand gestures to enable the operator to perform movements and monitor tasks from a distance.

Nocardia infection in solid organ transplant recipients: a multicenter European case-control study.

BACKGROUND  Nocardiosis is a rare, life-threatening opportunistic infection, affecting 0.04% to 3.5% of patients after solid organ transplantation (SOT). The aim of this study was to identify risk factors for Nocardia infection after SOT and to describe the presentation of nocardiosis in these patients. METHODS  We performed a retrospective case-control study of adult patients diagnosed with nocardiosis after SOT between 2000 and 2014 in 36 European (France, Belgium, Switzerland, Netherlands, Spain) centers. Two control subjects per case were matched by institution, transplant date and transplanted organ. A multivariable analysis was performed using conditional logistic regression to identify risk factors for nocardiosis. RESULTS  One hundred and seventeen cases of nocardiosis and 234 control patients were included. Nocardiosis occurred at a median of 17.5 [range 2-244] months after transplantation. In multivariable analysis, high calcineurin inhibitor trough levels in the month before diagnosis (OR=6.11 [2.58-14.51]), use of tacrolimus (OR=2.65 [1.17-6.00]) and corticosteroid dose (OR=1.12 [1.03-1.22]) at the time of diagnosis, patient age (OR=1.04 [1.02-1.07]) and length of stay in intensive care unit after SOT (OR=1.04 [1.00-1.09]) were independently associated with development of nocardiosis; low-dose cotrimoxazole prophylaxis was not found to prevent nocardiosis. Nocardia farcinica was more frequently associated with brain, skin and subcutaneous tissue infections than were other Nocardia species. Among the 30 cases with central nervous system nocardiosis, 13 (43.3%) had no neurological symptoms. CONCLUSIONS  We identified five risk factors for nocardiosis after SOT. Low-dose cotrimoxazole was not found to prevent Nocardia infection. These findings may help improve management of transplant recipients.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Probability distribution modelling to improve stability in nonlinear MIMO control

We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

Glycemic control: Risk factors, quality of life, workforce participation, and mortality among US adults with type 2 diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, (1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) .7%), borderline (HbA1c 7-8.9%), and poor (HbA1c .9%) glycemic control and potentially new risk factors (e.g. work characteristics), and (2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and (3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.^

Glycemic Control: Risk Factors, Quality of Life, Workforce Participation, and Mortality Among US Adults with Type 2 Diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, 1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) ≥7%), borderline (HbA1c 7-8.9%), and poor (HbA1c ≥9%) glycemic control and potentially new risk factors (e.g. work characteristics), and 2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and 3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.

Estudo comparativo de diferentes sistemas de injeção de vapor aplicados à remediação de solos contaminados por diesel

Among the potentially polluting economic activities that compromise the quality of soil and groundwater stations are fuel dealers. Leakage of oil derived fuels in underground tanks or activities improperly with these pollutants can contaminate large areas, causing serious environmental and toxicological problems. The number of gas stations grew haphazardly, without any kind of control, thus the environmental impacts generated by these enterprises grew causing pollution of soil and groundwater. Surfactants using various techniques have been proposed to remedy this kind of contamination. This study presents innovation as the application of different systems containing surfactant in the vapor phase and compares their diesel removal efficiencies of soil containing this contaminant. For this, a system that contains seven injection wells the following vaporized solutions: water, surfactant solution, microemulsion and nanoemulsion, The surfactants used were saponified coconut oil (OCS), in aqueous solution and an ethoxylated alcohol UNTL-90: aqueous solution , and nanoemulsion and microemulsion systems. Among the systems investigated, the nanoemulsion showed the highest efficiency, achieving 88% removal of residual phase diesel, the most ecologically and technically feasible by a system with lower content of active matter

Proteção em sistemas elétricos com geração distribuída utilizando a transformada wavelet

A typical electrical power system is characterized by centr alization of power gene- ration. However, with the restructuring of the electric sys tem, this topology is changing with the insertion of generators in parallel with the distri bution system (distributed gene- ration) that provides several benefits to be located near to e nergy consumers. Therefore, the integration of distributed generators, especially fro m renewable sources in the Brazi- lian system has been common every year. However, this new sys tem topology may result in new challenges in the field of the power system control, ope ration, and protection. One of the main problems related to the distributed generati on is the islanding formation, witch can result in safety risk to the people and to the power g rid. Among the several islanding protection techniques, passive techniques have low implementation cost and simplicity, requiring only voltage and current measuremen ts to detect system problems. This paper proposes a protection system based on the wavelet transform with overcur- rent and under/overvoltage functions as well as infomation of fault-induced transients in order to provide a fast detection and identification of fault s in the system. The propo- sed protection scheme was evaluated through simulation and experimental studies, with performance similar to the overcurrent and under/overvolt age conventional methods, but with the additional detection of the exact moment of the fault.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Avaliação sistemática de uma abordagem para integração de funcionalidades em sistemas web clonados

The software product line engineering brings advantages when compared with the traditional software development regarding the mass customization of the system components. However, there are scenarios that to maintain separated clones of a software system seems to be an easier and more flexible approach to manage their variabilities of a software product line. This dissertation evaluates qualitatively an approach that aims to support the reconciliation of functionalities between cloned systems. The analyzed approach is based on mining data about the issues and source code of evolved cloned web systems. The next step is to process the merge conflicts collected by the approach and not indicated by traditional control version systems to identify potential integration problems from the cloned software systems. The results of the study show the feasibility of the approach to perform a systematic characterization and analysis of merge conflicts for large-scale web-based systems.

Controle de mobilidade infraestruturado e orientado à qualidade para maximização de admissões em sistemas WiNeMO: uma abordagem definida por software

The spread of wireless networks and growing proliferation of mobile devices require the development of mobility control mechanisms to support the different demands of traffic in different network conditions. A major obstacle to developing this kind of technology is the complexity involved in handling all the information about the large number of Moving Objects (MO), as well as the entire signaling overhead required to manage these procedures in the network. Despite several initiatives have been proposed by the scientific community to address this issue they have not proved to be effective since they depend on the particular request of the MO that is responsible for triggering the mobility process. Moreover, they are often only guided by wireless medium statistics, such as Received Signal Strength Indicator (RSSI) of the candidate Point of Attachment (PoA). Thus, this work seeks to develop, evaluate and validate a sophisticated communication infrastructure for Wireless Networking for Moving Objects (WiNeMO) systems by making use of the flexibility provided by the Software-Defined Networking (SDN) paradigm, where network functions are easily and efficiently deployed by integrating OpenFlow and IEEE 802.21 standards. For purposes of benchmarking, the analysis was conducted in the control and data planes aspects, which demonstrate that the proposal significantly outperforms typical IPbased SDN and QoS-enabled capabilities, by allowing the network to handle the multimedia traffic with optimal Quality of Service (QoS) transport and acceptable Quality of Experience (QoE) over time.

Escala diagramática e influência de sistemas de produção na ocorrência do crestamento gomoso da melancia

CHAPTER 1 - The gummy stem blight, caused by the fungus D. bryoniae, is a disease commonly found in watermelon cultivated in several countries. In Brazil, there are numerous studies related to the disease, but there are not uniform methods for quantifying of disease severity in the field. Thus, we developed a diagrammatic scale based on scanned photos of watermelon leaves infected with D. bryoniae. The scale developed showed levels of 0; 10; 20; 45; 65 and 90% of severity. The scale validation was divided into two parts: initially, 10 evaluators (half with experienced and other half without experience) estimated the disease severity based on the initial observation of 100 photos of watermelon leaves with symptoms of the disease at different severity levels. Before, the same evaluators estimated the disease severity with the support of the scale prepared from the Quant program. Data were analyzed using linear regression and were obtained angular, linear, and correlation coefficients. Based on these data, we determined the accuracy and precision of the evaluations. The correlation coefficients (R2) ranged from 0.88 - 0.97 for the experienced evaluators and from 0.55 - 0.95 for the inexperienced evaluators. The average angular coefficient (A) for inexperienced evaluators was 20.42 and 8.61 with and without the support of diagrammatic scale, respectively. Experienced evaluators showed values of average linear coefficient of 5.30 and 1.68 with and without the support of diagrammatic scale, respectively. The absolute errors analysis indicated that the use of diagrammatic scale contributed to minimize the flaws in the severity levels estimation. The diagrammatic scale proposed shown adequate for gummy stem blight severity evaluation in watermelon. CHAPTER 2 - The gummy stem blight (Didymella bryoniae) is a disease that affects the productivity of watermelon leading to losses over 40%. This study aimed to evaluate the efficiency of different production systems in control of gummy stem blight in watermelon for to establish efficient methods to combat the disease. There were applied the following treatments: conventional tillage (T1), integrated management (T2) and organic management (T3). In T1 and T2 were applied mineral fertilization and T3 was used bovine manure. There was application of fungicides and insecticides in commercial dose in T1 and T2, being after soil chemical analysis in T2. Disease severity was assessed by grading scale. The experimental design was randomized blocks. The severity of gummy stem blight has increased substantially during the fruit formation. Watermelon plants grown with integrated management (T2) showed lower levels of disease severity, while plants in organic management (T3) exhibited higher levels of severity. We conclude that management based on judicious accompaniments in field represents best way to achieve the phytosanitary aspect adequate for cultivation of watermelon in Tocantins.

Estudo comparativo de dois conversores Boost quadrático com comutação suave monochaveados para aplicação de rastreamento de máxima potência em sistemas fotovoltaicos

This paper makes a comparative study of two Soft Single Switched Quadratic Boost Converters (SSS1 and SSS2) focused on Maximum Power Point Tracking (MPPT) of a PV array using Perturb and Observe (P&O) algorithm. The proposed converters maintain the static gain characteristics and dynamics of the original converter with the advantage of considerably reducing the switching losses and Electromagnetic Interference (EMI). It is displayed the input voltage Quadratic Boost converter modeling; qualitative and quantitative analysis of soft switching converters, defining the operation principles, main waveforms, time intervals and the state variables in each operation steps, phase planes of resonant elements, static voltage gain expressions, analysis of voltage and current efforts in semiconductors and the operational curves at 200 W to 800 W. There are presented project of PI, PID and PID + Notch compensators for MPPT closed-loop system and resonant elements design. In order to analyze the operation of a complete photovoltaic system connected to the grid, it was chosen to simulate a three-phase inverter using the P-Q control theory of three-phase instantaneous power. Finally, the simulation results and experimental with the necessary comparative analysis of the proposed converters will be presented.

Calidad y docencia universitaria en la sociedad del control. Aproximaciones analíticas

La presente comunicación pretende situar el análisis en torno a la universidad como objeto de análisis y de reflexión, considerando algunos ejes que nos permitan cuestionar (cuestionarnos) ciertas prácticas en relación con las políticas de evaluación de calidad universitaria - específicamente el Programa de Incentivos a la investigación- que se introdujeron en los sistemas de educación superior a partir de las reformas iniciadas en los años '90, en el marco de la consolidación de lo que algunos autores denominan el Estado Evaluador. En este marco, orientado por los ejes de calidad, desempeño y transparencia, se favoreció la creación de programas e instrumentos de evaluación que afectaron profundamente las dinámicas de la cotidianeidad de la docencia universitaria. El propósito de este trabajo reside en presentar algunas reflexiones acerca de los resultados de dichas estrategias de evaluación en la docencia universitaria que, desde la perspectiva aquí planteada, no solo no mejoran la calidad de la educación universitaria. sino que se constituyen en una serie de renovadas tecnologías de disciplinamiento y control que demarcarían nuevas zonas de inclusión /exclusión en el ámbito de la docencia universitaria