Development of a high‐resolution RGBW flexible display using a white organic light‐emitting diode with microcavity structure and that of a side‐roll touch panel

In this study, white organic electroluminescent devices with microcavity structures were developed. A flexible high‐resolution active‐matrix organic light‐emitting diode display with low power consumption using red, green, blue, and white sub‐pixels formed by a color‐filter method was fabricated. In addition, a side‐roll touch display was developed in combination with a capacitive flexible touch screen.     

Repeatedly foldable AMOLED display

In this study, a 5.9‐inch foldable active‐matrix organic light emitting diode (AMOLED) display was developed. A folding test was performed repeatedly. The display survived the folding test (100,000 folds) with a curvature radius of 2 mm. To protect an organic light emitting diode (OLED) against moisture, inorganic passivation layers are provided on the upper and lower sides of the flexible display. Using our transfer technology, high density passivation layers can be obtained. The measured water vapor transmission rate of the layer is 7 × 10^?6 g/m²?day or less, which improves OLED reliability. With these techniques, we have developed a book‐type display, which is repeatedly foldable like a book, and a tri‐fold display including a display area, which is foldable in three.     

On numerical solution of arbitrary symmetric linear systems by approximate orthogonalization

A very important class of inverse problems are those modelled by integral equations of the first kind. These equations are usually ill-conditioned, such that any discretization technique will produce an ill-conditioned system, in classical or least-squares formulation. For such kind of symmetric problems, we propose in this paper a stable iterative solver based on an approximate orthogonalization algorithm introduced by Z. Kovarik. We prove convergence of our algorithm for general symmetric least-squares problems and present some numerical experiments ilustrating its good behaviour on problems concerned with the determination of charge distribution generating a given electric field and gravity surveying, both modelled by first kind integral equations.     

Face Editing Using Part-Based Optimization of the Latent Space

We propose an approach for interactive 3D face editing based on deep generative models. Most of the current face modeling methods rely on linear methods and cannot express complex and non-linear deformations. In contrast to 3D morphable face models based on Principal Component Analysis (PCA), we introduce a novel architecture based on variational autoencoders. Our architecture has multiple encoders (one for each part of the face, such as the nose and mouth) which feed a single decoder. As a result, each sub-vector of the latent vector represents one part. We train our model with a novel loss function that further disentangles the space based on different parts of the face. The output of the network is a whole 3D face. Hence, unlike part-based PCA methods, our model learns to merge the parts intrinsically and does not require an additional merging process. To achieve interactive face modeling, we optimize for the latent variables given vertex positional constraints provided by a user. To avoid unwanted global changes elsewhere on the face, we only optimize the subset of the latent vector that corresponds to the part of the face being modified. Our editing optimization converges in less than a second. Our results show that the proposed approach supports a broader range of editing constraints and generates more realistic 3D faces.     

Multi-Scale Adaptive Sampling with Mobile Agents for Mapping of Forest Fires

The use of robotics in distributed monitoring applications requires wireless sensors that are deployed efficiently. A very important aspect of sensor deployment includes positioning them for sampling at locations most likely to yield information about the spatio-temporal field of interest, for instance, the spread of a forest fire. In this paper, we use mobile robots (agents) that estimate the time-varying spread of wildfires using a distributed multi-scale adaptive sampling strategy. The proposed parametric sampling algorithm, “EKF-NN-GAS” is based on neural networks, the extended Kalman filter (EKF), and greedy heuristics. It combines measurements arriving at different times, taken at different scale lengths, such as from ground, airborne, and spaceborne observation platforms. One of the advantages of our algorithm is the ability to incorporate robot localization uncertainty in addition to sensor measurement and field parameter uncertainty into the same EKF model. We employ potential fields, generated naturally from the estimated fire field distribution, in order to generate fire-safe trajectories that could be used to rescue vehicles and personnel. The covariance of the EKF is used as a quantitative information measure for sampling locations most likely to yield optimal information about the sampled field distribution. Neural net training is used infrequently to generate initial low resolution estimates of the fire spread parameters. We present simulation and experimental results for reconstructing complex spatio-temporal forest fire fields “truth models”, approximated by radial basis function (RBF) parameterizations. When compared to a conventional raster scan approach, our algorithm shows a significant reduction in the time necessary to map the fire field.     

Evidence for Irradiation Triggered Nonuniform Defects Distribution in Multiharmonic Magnetic Susceptibility of Neutron Irradiated YBa2Cu3O7?δ

Multiharmonic ac-magnetic susceptibility χ₁, χ₂, χ₃, of neutron irradiated Li-doped YBa₂Cu₃O_{7− x} has revealed a nonmonotonic dependence of all harmonics on the neutron fluence. The irradiation has a strongly depressive influence on the intergrain connection suggesting an increase of the effective thickness of the intergranular Josephson junction at a neutron fluence of 0.98 × 10¹⁷ cm⁻². Less damaged are the intragrain properties. A spectacular enhancement of the superconducting intragranular properties reflected in the characteristics of all harmonics was observed at highest fluence Φ = 9.98 × 10¹⁷ cm⁻². We assume that this effect results from the development of a space inhomogeneous distribution with alternating defectless and defect-rich regions.     

Environmental Fatigue and Static Behavior of RC Beams Strengthened with Carbon-Fiber-Reinforced Polymer

Many countries around the world have tremendous needs to repair and strengthen their transportation infrastructure. Almost everywhere, traffic loads have reached levels largely exceeding design expectations. Northern countries also experience severe winter conditions that are combined with an extensive use of deicing salts and accelerate structural deterioration. In Canada, the extent of deterioration has prompted many authorities, including the federal and provincial governments, to investigate the potential use of fiber-reinforced polymer products to extend the life of their existing structures. However, it is widely recognized that the large-scale implementation of these products is often impaired by the lack of data on their durability. This paper presents an experimental project undertaken in order to assess the durability of reinforced concrete beams externally strengthened with two types of carbon-fiber-reinforced polymer (CFRP). The beams were first exposed to either wet-dry cycles or continuous immersion in water and then were loaded in fatigue. Finally, they were tested quasi-statically under four-point bending up to failure. The test results presented here provide some insights on the potential long-term performance of CFRP-strengthened beams exposed to severe environmental conditions.     

Low-voltage improved accuracy Gaussian function generator with fourth-order approximation

An original realization of a CMOS Gaussian function generator is presented. The proposed method is based on a new approximation function that is able to fourth-order match the Gaussian function. The current-mode operation of the circuit strongly reduces the technological-caused errors and the errors introduced by temperature variations, with the result of an important increasing of the accuracy for the squaring circuit that represents the functional core of the Gaussian generator (0.1%). Additionally, the bandwidth of the generator is increased as a result of its current-mode operation. Because of the utilization of the new fourth-order approximation function, the deviation from the ideal Gaussian function is smaller than 1 dB for an extended range of the input variable. The circuit is designed for implementing in 0.18 μm CMOS technology, its proposed architecture being compatible with a low-voltage operation (V_DD=1 V). The proposed Gaussian function generator based on the new approximation function allows to extend its capability of generating any continuous mathematical functions, this feature being obtained by changing the approximation function coefficients.