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.     

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.     

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.     

Optimal-tuning PID control of adaptive materials for structural efficiency

The objective of this paper was solving the optimization problem of lightweight stiffened structures modelled as a two-dimensional domain in an efficient computational way. The underlying premise was that mass should be distributed in an efficient way, so as to use a minimum amount of material to accomplish the mechanical function. This premise was expressed as a global, multi-objective optimization problem in which stiffness and mass were conflicting objectives. Alternative local evolution rules were implemented to update mass density or Young’s modulus at each step of the iterative procedure. The solution of the structural optimization problem was accomplished by a novel automatic procedure consisting of two consecutive stages of control and optimization. In the first stage of Proportional Integral Derivative (PID) control gains were manually selected whereas in the second stage the finding of optimal values of control gains, target, and cost indices was allowed. In this study a bone-like material was adopted and a thin slab was analysed as a sample problem.     

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.     

Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions

We propose a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images, assuming that illumination conditions and cameras calibration are known in advance. Based on a variational framework and via gradient descents, the algorithm minimizes simultaneously and consistently a global cost functional with respect to both shape and reflectance. The motivations for our approach are threefold. (1) Contrary to previous works which mainly consider specific individual scenarios, our method applies indiscriminately to a number of classical scenarios; in particular it works for classical stereovision, multiview photometric stereo and multiview shape from shading. It works with changing as well as static illumination. (2) Our approach naturally combines stereo, silhouette and shading cues in a single framework. (3) Moreover, unlike most previous methods dealing with only Lambertian surfaces, the proposed method considers general dichromatic surfaces. We verify the method using various synthetic and real data sets.     

A Semantic Proof of Polytime Soundness of Light Affine Logic

We define realizability semantics for Light Affine Logic ( LAL\mathsf{LAL} ) which has the property that denotations of functions are polynomial time computable by construction of the model. This gives a new proof of polytime-soundness of LAL\mathsf{LAL} which is considerably simpler than the standard proof based on proof nets and is entirely semantical in nature. The model construction uses a new instance of a resource monoid; a general method for interpreting systems based on Linear Logic introduced earlier by the authors.