Investigation of wall-slip effect on lead-free solder paste and isotropic conductive adhesives

Wall-slip plays an important role in characterising the flow behaviour of solder paste materials. The wall slip arises due to the various attractive and repulsive forces acting between the solder particles and the walls of the measuring geometry.These interactions could lead to the presence of a thin solvent layer adjacent to the wall, which gives rise to slippage. The wall slip effect can play an important role in ensure successfulpaste release after the printing process. Wall-slip plays animportant role in characterising the flow behaviour of solderpastes and isotropic conductive adhesives. The study investigates the wall-slip formation in solder paste andisotropic conductive adhesives using flow visualisation technique. The slip distance was measured for parallel plate with different surface roughness in order to quantify the wallslip formations in these paste materials. An ink marker line was drawn between the parallel plate and the free surface of the sample. The parallel was rotated slowly at a constant shear rate of 0.05 sec-1 and the displacement of the ink marker was observed using a video microscope and image capturing software was utilised to capture the displacement of ink marker. From this study, it was found that the wall-slip effect was evident in all the paste materials. In addition, the different surface roughness of the parallel plates did not prevent the formation of wall-slip. This study has revealed that the wallslip effect could used to understand the flow behaviour of the paste in the stencil printing process.

The use of Raman microscopy to determine and localize vitamin E in biological samples

Alpha-tocopherol (aT), the predominant form of vitamin E in mammals, is thought to prevent oxidation of polyunsaturated fatty acids. In the lung, aT is perceived to be accumulated in alveolar type II cells and secreted together with surfactant into the epithelial lining fluid. Conventionally, determination of aT and related compounds requires extraction with organic solvents. This study describes a new method to determine and image the distribution of aT and related compounds within cells and tissue sections using the light-scattering technique of Raman microscopy to enable high spatial as well as spectral resolution. This study compared the nondestructive analysis by Raman microscopy of vitamin E, in particular aT, in biological samples with data obtained using conventional HPLC analysis. Raman spectra were acquired at spatial resolutions of 2-0.8 microm. Multivariate analysis techniques were used for analyses and construction of corresponding maps showing the distribution of aT, alpha-tocopherol quinone (aTQ), and other constituents (hemes, proteins, DNA, and surfactant lipids). A combination of images enabled identification of colocalized constituents (heme/aTQ and aT/surfactant lipids). Our data demonstrate the ability of Raman microscopy to discriminate between different tocopherols and oxidation products in biological specimens without sample destruction. By enabling the visualization of lipid-protein interactions, Raman microscopy offers a novel method of investigating biological characterization of lipid-soluble compounds, including those that may be embedded in biological membranes such as aT.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Hidden Conditional Random Fields for Visual Speech Recognition

In this paper we present the application of Hidden Conditional Random Fields (HCRFs) to modelling speech for visual speech recognition. HCRFs may be easily adapted to model long range dependencies across an observation sequence. As a result visual word recognition performance can be improved as the model is able to take more of a contextual approach to generating state sequences. Results are presented from a speaker-dependent, isolated digit, visual speech recognition task using comparisons with a baseline HMM system. We firstly illustrate that word recognition rates on clean video using HCRFs can be improved by increasing the number of past and future observations being taken into account by each state. Secondly we compare model performances using various levels of video compression on the test set. As far as we are aware this is the first attempted use of HCRFs for visual speech recognition.

Confounds in pictorial sets: The role of complexity and familiarity in basic-level picture processing

Complexity is conventionally defined as the level of detail or intricacy contained within a picture. The study of complexity has received relatively little attention-in part, because of the absence of an acceptable metric. Traditionally, normative ratings of complexity have been based on human judgments. However, this study demonstrates that published norms for visual complexity are biased. Familiarity and learning influence the subjective complexity scores for nonsense shapes, with a significant training x familiarity interaction [F(1,52) = 17.53, p <.05]. Several image-processing techniques were explored as alternative measures of picture and image complexity. A perimeter detection measure correlates strongly with human judgments of the complexity of line drawings of real-world objects and nonsense shapes and captures some of the processes important in judgments of subjective complexity, while removing the bias due to familiarity effects.

Music, Magic, and the Mythic: The Dynamics of Visual and Aural Discourse in Souleymane Cissé’s Yeelen

The 1980s saw a wave of African films that aimed to represent, on both local and international screens, a sophisticated pre-colonial Africa, thus debunking notions of the continent as primitive. Toward this aim the films inscribed the conventions of oral performance within their visual styles, denying spectator identification with the protagonists and emphasising the presence of the narrator. However, some critics argued that these films exoticised Africa, while their use of oral performance’s distancing effect echoed the ‘scientific’ distance structured by the ethnographic film, in which African societies were represented as ‘the other’. Souleymane Cissé’s Yeelen exemplifies this tension, transposing into cinematic form oral storytelling techniques in the depiction of a power struggle within the covert cult of the komo, a Bambara initiation society unfamiliar to most non-Bambara viewers. This paper demonstrates how the film negotiates this tension via music, which interpellates the international spectator by eliciting a greater identification with the protagonists than that determined at a visual level, while encoding a verisimilitude to rituals that may otherwise be read as the superstitious practices of ‘the other’. In this way, music and image in Yeelen operate as parallel, though often overlapping, discourses, bridging the gap between the film’s culturally specific narrative and formal components, and its international spectators.

Endothelin-like immunoreactivity and receptor binding in the choroid and retina

This study has examined the localisation and receptor-binding of the endothelins in retina and choroid of human and rat origin. Immunoreactivity to anti-ET1 and anti-ET3 was investigated in trypsin digests, frozen sections and ultrathin sections using immunocytochemistry and immunogold labelling techniques. In addition, receptor binding of 125I-ET1 and 125I-ET3 was visualised and quantified using autoradiography and image analysis. Intense immunoreactivity to anti-ET1 and anti-ET3 was observed in the photoreceptor inner segments and in the outer plexiform layer (OPL) of human and rat retina. Ultrastructural localisation using immunogold labelling confirmed the presence of ET1 and ET3 in the photoreceptor cells. In retinal vascular digests, ET1 was visualised in the arteries, arterioles and at the pre-arteriolar sphincters, however, immunoreactivity to anti-ET3 was absent in the retinal vasculature. Both ETA and ETB-type receptor binding sites to 125I-ET1 and 125I-ET3 were detected in the vascular smooth muscle of choroidal and retinal vessels with the former being predominant. Extravascular binding sites of the ETB-type were found in the ganglion cell layer.

AdaBoost Multiple Feature Selection and Combination for Face Recognition

Gabor features have been recognized as one of the most successful face representations. Encouraged by the results given by this approach, other kind of facial representations based on Steerable Gaussian first order kernels and Harris corner detector are proposed in this paper. In order to reduce the high dimensional feature space, PCA and LDA techniques are employed. Once the features have been extracted, AdaBoost learning algorithm is used to select and combine the most representative features. The experimental results on XM2VTS database show an encouraging recognition rate, showing an important improvement with respect to face descriptors only based on Gabor filters.

Automatic detection and classification of football players

Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.

Rao-blackwellized particle filter for human appearance and position tracking

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.

The Absent Image in Electronic Music

A survey of the after-effects of recording technology on media arts, particularly in the digital age. The article covers a wide variety of sound artists, including work by the author.

Mean shift based gradient vector flow for image segmentation

In recent years, gradient vector flow (GVF) based algorithms have been successfully used to segment a variety of 2-D and 3-D imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods may lead to biased segmentation results. In this paper, we propose MSGVF, a mean shift based GVF segmentation algorithm that can successfully locate the correct borders. MSGVF is developed so that when the contour reaches equilibrium, the various forces resulting from the different energy terms are balanced. In addition, the smoothness constraint of image pixels is kept so that over- or under-segmentation can be reduced. Experimental results on publicly accessible datasets of dermoscopic and optic disc images demonstrate that the proposed method effectively detects the borders of the objects of interest.