Generalized linear mixed model with a penalized Gaussian mixture as a random effects distribution

Generalized linear mixed models are popular for regressing a discrete response when there is clustering, e.g. in longitudinal studies or in hierarchical data structures. It is standard to assume that the random effects have a normal distribution. Recently, it has been examined whether wrongly assuming a normal distribution for the random effects is important for the estimation of the fixed effects parameters. While it has been shown that misspecifying the distribution of the random effects has a minor effect in the context of linear mixed models, the conclusion for generalized mixed models is less clear. Some studies report a minor impact, while others report that the assumption of normality really matters especially when the variance of the random effect is relatively high. Since it is unclear whether the normality assumption is truly satisfied in practice, it is important that generalized mixed models are available which relax the normality assumption. A replacement of the normal distribution with a mixture of Gaussian distributions specified on a grid whereby only the weights of the mixture components are estimated using a penalized approach ensuring a smooth distribution for the random effects is proposed. The parameters of the model are estimated in a Bayesian context using MCMC techniques. The usefulness of the approach is illustrated on two longitudinal studies using R-functions.     

Post-buckling dynamic behavior of self-assembled 3D microstructures

The paper presents the snap-through phenomenon in the case of micro fabricated clamped-clamped buckled beam. This dynamic post-buckling behavior is likely to occur in 3D microstructures when they are subjected to large vibration amplitudes. The main difference between this work and previous studies is the MEMS specific beam dimension, especially the large initial deflection of the buckled beam that involves the inversion of the two first resonance frequencies. The mathematical development allows showing how the vibration amplitude of the supporting base affects the post-buckling dynamic behavior of the beam. For each frequency, the limit between the stable behavior and the snap-through behavior is evaluated. Moreover, the effect of environment is taken into account from the damping point of view. Samples are fabricated and the experiment is described. Measurements are compared to the theoretical approach and the results are in good agreement with the proposed model.     

Introductory programming and young learners with visual disabilities: a review

Universal Access in the Information Society - Computational Thinking (CT) captures the mental processes used to model and solve problems using a computational processes. While often connected to...     

Workload assignment for global real-time scheduling on unrelated clustered platforms

Real-Time Systems - Heterogeneous MPSoCs are being used more and more, from cellphones to critical embedded systems. Most of those systems offer heterogeneous sets of identical cores. In this...     

Neural network classifier and multiple hypothesis image segmentation for dietary assessment using calorie calculator

Nowadays, dietary assessment becomes the emerging system for evaluating the person’s food intake. In this paper, the multiple hypothesis image segmentation and feed-forward neural network classifier are proposed for dietary assessment to enhance the performance. Initially, the segmentation is applied to input image which is used to determine the regions where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the significant feature of food items is extracted by the global feature and local feature extraction method. After the features are obtained, the classification is performed for each segmented region using feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food area volume and (ii) calorie and nutrition measure based on mass value. The outcome of the proposed method attains 96% of accuracy value which provides the better classification performance.     

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer‐sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.     

Microstructure evolution and thermoelectric properties of Te-poor and Te-rich (Bi,Sb)<Subscript>2</Subscript>Te<Subscript>3</Subscript> prepared via solidification

This paper explores in detail, the microstructures and thermoelectric properties of Te-rich and Te-poor (Bi,Sb)₂Te₃ alloys. We show that tuning the composition of ternary Bi–Sb–Te type alloys allows us to synthesize a range of microstructures containing a primary solid solution of (Bi,Sb)₂Te₃ with varying amounts of Te solid solution or a (Bi,Sb)Te compound. Te exists as a constituent of the multilayer domain while (Bi,Sb)Te appears in the thin intercellular regions of the (Bi,Sb)₂Te₃ dendritic cells. The presence of Te imparts an n-type behavior to the composite while the (Bi,Sb)₂Te₃ with a small amount of (Bi,Sb)Te exhibits p-type properties. A maximum ZT value of ≈0.4 at 425 K was achieved, opening up the possibility of using these alloys for thermoelectric device applications.     

63Cu NMR in the normal state of HgBa2Ca2Cu3O8+δ

We present a⁶³Cu NMR study of HgBa₂Ca₂Cu₃O₈₊ underdoped single crystals with T_c 115 K. While the uniform spin susceptibility decreases below T_o 370 K, relaxation rate measurements demonstrate the opening of a spingap at Q = (, ) below T* 230 K, the highest temperature reported so far. The characteristic energy of spin fluctuations is shown to be higher than in underdoped YBa₂Cu₃O_7–, and the analysis of the quadrupole and hyperfine couplings suggests that the in-plane Cu-O hybridization is also stronger. The T-dependence of T₁ is the same in the three CuO₂ planes which seems hardly compatible with the pure interlayer spin-pairing picture.     

Indexing and querying segmented web pages: the BlockWeb Model

We present in this paper a model for indexing and querying web pages, based on the hierarchical decomposition of pages into blocks. Splitting up a page into blocks has several advantages in terms of page design, indexing and querying such as (i) blocks of a page most similar to a query may be returned instead of the page as a whole (ii) the importance of a block can be taken into account, as well as (iii) the permeability of the blocks to neighbor blocks: a block b is said to be permeable to a block b?? in the same page if b?? content (text, image, etc.) can be (partially) inherited by b upon indexing. An engine implementing this model is described including: the transformation of web pages into blocks hierarchies, the definition of a dedicated language to express indexing rules and the storage of indexed blocks into an XML repository. The model is assessed on a dataset of electronic news, and a dataset drawn from web pages of the ImagEval campaign where it improves by 16% the mean average precision of the baseline.     

Moving People Segmentation from Zoomed Dynamic Scenes Containing a Door

The challenge of segmenting the moving object is harder when the background is dynamic and the camera used can change its zoom dynamically. Here, in this paper, we propose a method to detect and segment moving object from a dynamic background, which contains moving multiple-leaf doors. In addition, the proposed algorithm also takes care of dynamic zoom changes that can occur while shooting a scene. The proposed method uses background-rebuilding with discrete door’s position to tackle moving multiple-leaf door backgrounds and image feature comparison to tackle changes in zoom. The experiment results show satisfying segmentation results with high processing speed.