A compact and high-resolution version of a capacitively coupled contactless conductivity detector

An all-in-one version of a capacitively coupled contactless conductivity detector is introduced. The absence of moving parts (potentiometers and connectors) makes it compact (6.5 cm(3)) and robust. A local oscillator, working at 1.1 MHz, was optimized to use capillaries of id from 20 to 100 lam. Low noise circuitry and a high-resolution analog-to-digital converter (ADC) (21 bits effective) grant good sensitivities for capillaries and background electrolytes currently used in capillary electrophoresis. The fixed frequency and amplitude of the signal generator is a drawback that is compensated by the steady calibration curves for conductivity. Another advantage is the possibility of determining the inner diameter of a capillary by reading the ADC when air and subsequently water flow through the capillary. The difference of ADC reading may be converted into the inner diameter by a calibration curve. This feature is granted by the 21-bit ADC, which eliminates the necessity of baseline compensation by hardware. In a typical application, the limits of detection based on the 3 sigma criterion (without baseline filtering) were 0.6, 0.4, 0.3, 0.5, 0.6, and 0.8 mu mol/L for K(+), Ba(2+), Ca(2+), Na(+), Mg(2+), and Li(+), respectively, which is comparable to other high-quality implementations of a capacitively coupled contactless conductivity detector.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Uma avaliacão fenomenográfica dos cursos suecos baseados na web

O propósito deste texto é discutir a avaliação de um curso superior oferecido por uma universidade sueca. Para tanto, parti de uma análise das avaliações feitas pelos estudantes, no ano de 2011-2012, quanto ao conteúdo, as aulas ministrada e a relação estabelecida entre o professor e os estudantes. O curso analisado foi o de Brasil Contemporâneo, da Universidade de Dalarna. O curso é oferecido na forma EBW e faz parte da graduação em Português.       As conclusões alcançadas e fundamentadas na análise do questionários  apontam para uma necessidade de uma sistematização do conteúdo e de uma melhor exposição do mesmo. Os estudantes, na sua maoria estrangeiros, têm uma percepção sobre a realidade brasileira que ao se contrapor à literatura do curso leva-os a reverem e a redefinirem a imagem que os mesmos tinham sobre o Brasil. Entrentanto, as avaliações apontam para a necessidade de desenvolvimento e formento de trabalhos em grupos que auxiliam na aprendizagem dos estudantes. Esta é um importante desáfio dos cursos baseados na Web, na rede de ensino superior sueca.