A review of smart homes- present state and future challenges

In the era of information technology, the elderly and disabled can be monitored with numerous intelligent devices. Sensors can be implanted into their home for continuous mobility assistance and non-obtrusive disease prevention. Modern sensor-embedded houses, or smart houses, cannot only assist people with reduced physical functions but help resolve the social isolation they face. They are capable of providing assistance without limiting or disturbing the resident's daily routine, giving him or her greater comfort, pleasure, and well-being. This article presents an international selection of leading smart home projects, as well as the associated technologies of wearable/implantable monitoring systems and assistive robotics. The latter are often designed as components of the larger smart home environment. The paper will conclude by discussing future challenges of the domain.     

Minimising total tardiness in the m-machine flowshop problem: A review and evaluation of heuristics and metaheuristics

In this work, a review and comprehensive evaluation of heuristics and metaheuristics for the m-machine flowshop scheduling problem with the objective of minimising total tardiness is presented. Published reviews about this objective usually deal with a single machine or parallel machines and no recent methods are compared. Moreover, the existing reviews do not use the same benchmark of instances and the results are difficult to reproduce and generalise. We have implemented a total of 40 different heuristics and metaheuristics and we have analysed their performance under the same benchmark of instances in order to make a global and fair comparison. In this comparison, we study from the classical priority rules to the most recent tabu search, simulated annealing and genetic algorithms. In the evaluations we use the experimental design approach and careful statistical analyses to validate the effectiveness of the different methods tested. The results allow us to clearly identify the state-of-the-art methods.     

Understanding users and their needs

Gaze-control enables people to control a computer by using eye-gaze to select items on screen. Gaze-control is a necessity for people who have lost all motor control of their body and only have control over eye movements. In addition, gaze-control can be the quickest and least tiring option for a far broader group of people with varying disabilities. This paper reports findings from gaze-control user trials involving users from both groups: people who are totally paralyzed, as well as people with a wide range of complex disabilities. The trials conducted involved four different centres supporting people with disabilities in three different European countries. Several gaze-control systems were trialled by a large number of users with varying needs and abilities. The perceived benefits of gaze-control are described, and recommendations for successful assessment and implementation of gaze-control are provided.     

Multi-Stage Phase-Segregation of Mixed Halide Perovskites under Illumination: A Quantitative Comparison of Experimental Observations and Thermodynamic Models

Photo- and charge-carrier-induced ion migration is a major challenge when utilizing metal halide perovskite semiconductors for optoelectronic applications. For mixed iodide/bromide perovskites, the compositional instability due to light- or electrical bias induced phase-segregation restricts the exploitation of the entire bandgap range. Previous experimental and theoretical work suggests that excited states or charge carriers trigger the process, but the exact mechanism is still under debate. To identify the mechanism and cause of light-induced phase-segregation phenomena, the full compositional range of methylammonium lead bromide/iodide samples are investigated, MAPb(Br_xI_1-x)₃ with x = 0…1, by simultaneous in situ X-ray diffraction (XRD) and photoluminescence (PL) spectroscopy during illumination. The quantitative comparison of composition-dependent in situ XRD and PL shows that at excitation densities of 1 sun, only the initial stage of photo-segregation is rationalized with the previously established thermodynamic models. However, a progression of the phase segregation is observed that is rationalized by considering long-lived accumulative photo-induced material alterations. It is suggested that (additional) photo-induced defects, possibly halide vacancies and interstitials, need to be considered to fully rationalize light-induced phase segregation and anticipate the findings to provide crucial insight for the development of more sophisticated models.     

Covalent Adaptable Microstructures via Combining Two-Photon Laser Printing and Alkoxyamine Chemistry: Toward Living 3D Microstructures

Manufacturing programmable materials, whose mechanical properties can be adapted on demand, is highly desired for their application in areas ranging from robotics, to biomedicine, or microfluidics. Herein, the inclusion of dynamic and living bonds, such as alkoxyamines, in a printable formulation suitable for two-photon 3D laser printing is exploited. On one hand, taking advantage of the dynamic covalent character of alkoxyamines, the nitroxide exchange reaction is investigated. As a consequence, a reduction of the Young´s Modulus by 50%, is measured by nanoindentation. On the other hand, due to its “living” characteristic, the chain extension becomes possible via nitroxide mediated polymerization. In particular, living nitroxide mediated polymerization of styrene results not only in a dramatic increase of the volume (≈8 times) of the 3D printed microstructure but also an increase of the Young's Modulus by two orders of magnitude (from 14 MPa to 2.7 GPa), while maintaining the shape including fine structural details. Thus, the approach introduces a new dimension by enabling to create microstructures with dynamically tunable size and mechanical properties.     

Non-Hierarchical Architected Materials with Extreme Stiffness and Strength

Stretch-dominated truss and plate microstructures are contenders in the quest for realizing architected materials with extreme stiffness and strength. In the low volume fraction limit, closed-cell isotropic plate microstructures meet theoretical upper bounds on stiffness but have low buckling strength, whereas open-cell truss microstructures have high buckling strength at the cost of significantly reduced stiffness. At finite volume fractions, the picture becomes less clear but both are outperformed by hollow truss lattice and hierarchical microstructures in terms of buckling strength. Despite significant advances in manufacturing methods, hollow and multi-scale hierarchical microstructures are still challenging to build. The question is if there exist realizable microstructures providing stiffness and strength matching or even beating hard-to-realize hollow or hierarchical microstructures? Herein, single-scale non-hierarchical (first order) microstructures that beat the buckling strength of hollow truss lattice structures by a factor of 2.4 and first- and second-order plate microstructures by factors of 5 and 1.4, respectively, are systematically designed, built, and tested. Stiffness of the microstructures is within 40% of theoretical bounds and beats both truss and second order plate microstructures. The microstructures are realized with 3D printing. Experiments validate theoretical predictions and additional insight is provided through numerical modeling of a CT-scanned sample.     

Distance-based local linear regression for functional predictors

The problem of nonparametrically predicting a scalar response variable from a functional predictor is considered. A sample of pairs (functional predictor and response) is observed. When predicting the response for a new functional predictor value, a semi-metric is used to compute the distances between the new and the previously observed functional predictors. Then each pair in the original sample is weighted according to a decreasing function of these distances. A Weighted (Linear) Distance-Based Regression is fitted, where the weights are as above and the distances are given by a possibly different semi-metric. This approach can be extended to nonparametric predictions from other kinds of explanatory variables (e.g., data of mixed type) in a natural way.