Context-sensitive dynamic ordinal regression for intensity estimation of facial action units

Modeling intensity of facial action units from spontaneously displayed facial expressions is challenging mainly because of high variability in subject-specific facial expressiveness, head-movements, illumination changes, etc. These factors make the target problem highly context-sensitive. However, existing methods usually ignore this context-sensitivity of the target problem. We propose a novel Conditional Ordinal Random Field (CORF) model for context-sensitive modeling of the facial action unit intensity, where the W5+ (who, when, what, where, why and how) definition of the context is used. While the proposed model is general enough to handle all six context questions, in this paper we focus on the context questions: who (the observed subject), how (the changes in facial expressions), and when (the timing of facial expressions and their intensity). The context questions who and howare modeled by means of the newly introduced context-dependent covariate effects, and the context question when is modeled in terms of temporal correlation between the ordinal outputs, i.e., intensity levels of action units. We also introduce a weighted softmax-margin learning of CRFs from data with skewed distribution of the intensity levels, which is commonly encountered in spontaneous facial data. The proposed model is evaluated on intensity estimation of pain and facial action units using two recently published datasets (UNBC Shoulder Pain and DISFA) of spontaneously displayed facial expressions. Our experiments show that the proposed model performs significantly better on the target tasks compared to the state-of-the-art approaches. Furthermore, compared to traditional learning of CRFs, we show that the proposed weighted learning results in more robust parameter estimation from the imbalanced intensity data

Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity

Joint modeling of the intensity of facial action units (AUs) from face images is challenging due to the large number of AUs (30+) and their intensity levels (6). This is in part due to the lack of suitable models that can efficiently handle such a large number of outputs/classes simultaneously, but also due to the lack of labelled target data. For this reason, majority of the methods proposed so far resort to independent classifiers for the AU intensity. This is suboptimal for at least two reasons: the facial appearance of some AUs changes depending on the intensity of other AUs, and some AUs co-occur more often than others. Encoding this is expected to improve the estimation of target AU intensities, especially in the case of noisy image features, head-pose variations and imbalanced training data. To this end, we introduce a novel modeling framework, Copula Ordinal Regression (COR), that leverages the power of copula functions and CRFs, to detangle the probabilistic modeling of AU dependencies from the marginal modeling of the AU intensity. Consequently, the COR model achieves the joint learning and inference of intensities of multiple AUs, while being computationally tractable. We show on two challenging datasets of naturalistic facial expressions that the proposed approach consistently outperforms (i) independent modeling of AU intensities, and (ii) the state-ofthe-art approach for the target task

Novel High-Frequency Electrical Characterization Technique for Magnetic Passive Devices.

Integrated magnetic components are key elements of the power supply on chip modules. Due to the application requirements, these magnetic devices work at very high frequency and have low inductances. Conventional small-signal tests do not provide all the required information about the magnetic device. Hence, it is important to develop new setups to apply large signals to accurately measure the performance of devices under realistic operating conditions, including nonlinear core effects. The proposed experimental setup is suitable to measure the device impedance under different large-signal test conditions, similar to those in the actual converter, since the excitation current can be configured through every winding: ac current up to 0.5 A at frequencies up to 120 MHz and dc bias current up to 2 A through one or both windings. Voltage and current are measured using commercial instrumentation. Due to the characteristics of the probes and the high frequency of the test, the attenuation and delay due to the probes and the experimental setup have to be taken into account when processing the voltage and current waveforms to calculate the impedances. The compensation test to calculate this attenuation and delay is described. Finally, the proposed setup is validated by measuring a two-phase coupled inductor microfabricated on silicon.This work was supported in part by the European Union through FP7 (Project: PowerSwipe) under Grant 318529, in part by the Science Foundation Ireland through the Investigators Programme under Grant 15/IA/3180, and in part by the Spanish Ministry of Economy and Competitiveness and FEDER funds under Project DPI2014-53685-C2-1-R and Project DPI2017-88062-R. This paper was recommended for publication by Associate Editor Matthew A. Wilkowski

Eye movement analysis and cognitive assessment: the use of comparative visual search tasks in a non-immersive vr application

Background: An adequate behavioral response depends on attentional and mnesic processes. When these basic cognitive functions are impaired, the use of non-immersive Virtual Reality Applications (VRAs) can be a reliable technique for assessing the level of impairment. However, most non-immersive VRAs use indirect measures to make inferences about visual attention and mnesic processes (e.g., time to task completion, error rate). Objectives: To examine whether the eye movement analysis through eye tracking (ET) can be a reliable method to probe more effectively where and how attention is deployed and how it is linked with visual working memory during comparative visual search tasks (CVSTs) in non-immersive VRAs. Methods: The eye movements of 50 healthy participants were continuously recorded while CVSTs, selected from a set of cognitive tasks in the Systemic Lisbon Battery (SLB). Then a VRA designed to assess of cognitive impairments were randomly presented. Results: The total fixation duration, the number of visits in the areas of interest and in the interstimulus space, along with the total execution time was significantly different as a function of the Mini Mental State Examination (MMSE) scores. Conclusions: The present study demonstrates that CVSTs in SLB, when combined with ET, can be a reliable and unobtrusive method for assessing cognitive abilities in healthy individuals, opening it to potential use in clinical samples.info:eu-repo/semantics/submittedVersio

Changes in the concentrations and transcripts for gibberellins and other hormones in a growing leaf and roots of wheat seedlings in response to water restriction

Background Bread wheat (Triticum aestivum) is a major source of nutrition globally, but yields can be seriously compromised by water limitation. Redistribution of growth between shoots and roots is a common response to drought, promoting plant survival, but reducing yield. Gibberellins (GAs) are necessary for shoot and root elongation, but roots maintain growth at lower GA concentrations compared with shoots, making GA a suitable hormone for mediating this growth redistribution. In this study, the effect of progressive drought on GA content was determined in the base of the 4th leaf and root tips of wheat seedlings, containing the growing regions, as well as in the remaining leaf and root tissues. In addition, the contents of other selected hormones known to be involved in stress responses were determined. Transcriptome analysis was performed on equivalent tissues and drought-associated differential expression was determined for hormone-related genes. Results After 5 days of applying progressive drought to 10-day old seedlings, the length of leaf 4 was reduced by 31% compared with watered seedlings and this was associated with significant decreases in the concentrations of bioactive GA(1) and GA(4) in the leaf base, as well as of their catabolites and precursors. Root length was unaffected by drought, while GA concentrations were slightly, but significantly higher in the tips of droughted roots compared with watered plants. Transcripts for the GA-inactivating gene TaGA2ox4 were elevated in the droughted leaf, while those for several GA-biosynthesis genes were reduced by drought, but mainly in the non-growing region. In response to drought the concentrations of abscisic acid, cis-zeatin and its riboside increased in all tissues, indole-acetic acid was unchanged, while trans-zeatin and riboside, jasmonate and salicylic acid concentrations were reduced. Conclusions Reduced leaf elongation and maintained root growth in wheat seedlings subjected to progressive drought were associated with attenuated and increased GA content, respectively, in the growing regions. Despite increased TaGA2ox4 expression, lower GA levels in the leaf base of droughted plants were due to reduced biosynthesis rather than increased catabolism. In contrast to GA, the other hormones analysed responded to drought similarly in the leaf and roots, indicating organ-specific differential regulation of GA metabolism in response to drought

Applicability Evidence of Constructal Design in Structural Engineering: Case Study of Biaxial Elasto-Plastic Buckling of Square Steel Plates with Elliptical Cutout

The application of the Constructal Design method in Heat Transfer and Fluid Mechanics areas is an already consecrated approach to geometrically evaluate these flow engineering systems. However, this approach in Mechanics of Materials realm is not yet widely used, since one can find only few publications about it in literature. The Constructal Design is based on the Constructal Law, a physical law that explains the universal phenomenon of evolution of any finite size flow system. Therefore, the main goal here is to show that the Constructal Design can also be used in dedicated Structural Engineering problems as an effective method for geometric evaluation. The obtained results prove the Constructal Design applicability definitively in Mechanics of Materials

Constructal design method dealing with stiffened plates and symmetry boundaries

A new computational procedure for modelling the structural behavior of stiffened plates with symmetry boundary conditions is here presented. It uses two-dimensional finite elements as a way to decrease computational time without losing precision thanks to a relatively small number of elements applied for analyzing out-of-plane displacements (deflections) and stresses. Adding, the constructal design method was included in the procedure, together with the exhaustive search technique, with the scope to optimize the stress/strain status of stiffened plates by design changes. For the purpose, a reference plate without stiffeners was initially design and used as starting point. Part of the volume was reshaped into stiffeners: thickness was reduced maintaining unchanged weight, length and width. The main goal was to minimize strains and stresses by geometric changes. Results demonstrated that, thanks to this design procedure, it is always possible to find an adequate geometry transformation from reference plate into stiffeners, allowing significant improvements in mechanical behavior