Two‐way multi‐view 2‐D/3‐D display combining LC lens and HVxDP panel using novel pixel arrangement

We have developed a two‐way multi‐view 2‐D/3‐D display combining a liquid crystal lens and horizontally and vertically x times‐density pixels (HVxDP) arrangement. The two‐way multi‐view display features the same display resolution in 2‐D and 3‐D modes and a quite small color moiré for landscape and portrait, respectively, when using the HVxDP arrangement. In this paper, we realized suitable 3‐D properties for achieving a good balance between 3‐D moiré and 3‐D crosstalk for landscape and portrait by a two‐way liquid crystal lens with two kinds of focal lengths for the edge part and the center part of the lens.     

Rendering of HDR images to improve brightness discrimination

The impression of quality of images can be enhanced on a high dynamic range (HDR) displays. Generally, a conventional 8‐bit image can be processed to an HDR image by inverse tone mapping operators. Among the operators, brightness discrimination mapping by applying brightness adaptation model attempted to mimic the human visual system. In this paper, we use a brightness adaptation model to derive a brightness discrimination mapping algorithm for HDR displays. The proposed algorithm maximizes a function, which represents the local and global brightness discrimination range by exploiting characteristics of the human visual system. Enhancement of details is verified by visualizing HDR images from dark to bright regions. Improvement of dynamic range is quantified by measuring increased discrimination ratio.     

Partial consensus of identical feedforward dynamic systems with input saturations

This paper studies the partial consensus problem for identical feedforward dynamic systems with input saturations. We construct two consensus protocols using the partial‐state information and full‐state information, respectively. Applying a change of coordinates, feedforward system is transformed into the block diagonal form. Then, by utilizing the bounded real lemma and small gain theorem, we solve the partial consensus problem, and the existence of each protocol is derived. Copyright © 2015 John Wiley & Sons, Ltd.     

LTCC‐based monolithic system‐in‐package (SiP) module for millimeter‐wave applications

A miniature LTCC system‐in‐package (SiP) module has been presented for millimeter‐wave applications. A typical heterodyne 61 GHz transmitter (Tx) has been designed and fabricated in a type of the SiP module as small as 36 × 12 × 0.9 mm³. Five active chips including a mixer, driver amplifier, power amplifier, and two frequency multipliers were mounted on the single LTCC package substrate, in which all passive circuits such as a stripline (SL) BPF, 2 × 2 array patch antenna, surface‐mount technology (SMT) pads, and intermediate frequency (IF) feeding lines have been monolithically embedded by using vertical and planar transitions. The embedded SL BPF shows the center frequency of 60.8 GHz, BW of 4.1%, and insertion loss of 3.74 dB. The gain and 3‐dB beam width of the fabricated 2 × 2 array patch antenna are 7 dBi and 36 degrees, respectively. The assembled LTCC 61 GHz Tx SiP module achieves an output power of 10.2 dBm and an up‐conversion gain of 7.3 dB. Because of the integrated BPF, an isolation level between a local oscillation (LO) and RF signal is below 26.4 dBc and the spurious level is suppressed by lower than 22.4 dBc. By using a 61 GHz receiver (Rx) consisting of off‐the‐shelf modules, wireless communication test was demonstrated by comparing measured IF spectrums at the Tx and Rx part.     

High-quality image restoration from partial mixed adaptive-random measurements

A novel framework to construct an efficient sensing (measurement) matrix, called mixed adaptive-random (MAR) matrix, is introduced for directly acquiring a compressed image representation. The mixed sampling (sensing) procedure hybridizes adaptive edge measurements extracted from a low-resolution image with uniform random measurements predefined for the high-resolution image to be recovered. The mixed sensing matrix seamlessly captures important information of an image, and meanwhile approximately satisfies the restricted isometry property. To recover the high-resolution image from MAR measurements, the total variation algorithm based on the compressive sensing theory is employed for solving the Lagrangian regularization problem. Both peak signal-to-noise ratio and structural similarity results demonstrate the MAR sensing framework shows much better recovery performance than the completely random sensing one. The work is particularly helpful for high-performance and lost-cost data acquisition.     

Towards understanding the gamification upon users’ scores in a location-based social network

Online social platform, such as Wikipedia and Foursquare, has been increasingly exploded due to not only various useful services provided but also social gaming mechanisms that can keep users actively engaged. For example, users are awarded ”virtual goods” like badges and points when they contribute to the community in the network by voluntarily sharing ideas and other information. In this paper, we aim to examine the effectiveness of a social gamification mechanism, named user scores, designed in Foursquare which is one of most popular location-based social networks. A user’s score in Foursquare is an aggregate measure based on recent check-in activities of the user, which reflects a snapshot summary of the user’s temporal and spatial behaviors. Whenever a user checks in to a venue, a list of scores of the user’s friends are visible to the user via a ”leaderboard” which ranks these users’ scores in a descending order. Given a pair of friends who participate in a score competition in such a gimification mechanism, we identify if one user’s scores have significant influence on the other user’s scores by utilizing the Granger Causality Test. To understand what types of users and what types of friends tend to participate in the score competition (i.e., their check-ins are more likely driven by such a gamification mechanism), we extract users’ features (e.g. user’s degree) as well as the features of pairs of friends (e.g., number of common friends, score similarity and ranking difference) to examine whether these features have correlations with those pairs of users who are identified as being involved in the score game. The identified influence on user scores has the important implication on applications including friend and venue recommendations in location-based social networks.     

Trajectory Control of Snake‐Like Robots in Natural Oscillation

A class of body movement patterns called natural oscillation has been revealed to mimic the gaits observed in many animals. In this paper, we introduce an additional higher level control loop that is capable of manipulating a robot's motion orientation. With such a new orientation turning functionality, a snake‐like robot is able to achieve trajectory tracking while maintaining its body in a natural oscillation gait. The effectiveness of the control design is illustrated by some case studies with various trajectories.     

Quantum teleportation between a single-rail single-photon qubit and a coherent-state qubit using hybrid entanglement under decoherence effects

We study quantum teleportation between two different types of optical qubits using hybrid entanglement as a quantum channel under decoherence effects. One type of qubit employs the vacuum and single-photon states for the basis, called a single-rail single-photon qubit, and the other utilizes coherent states of opposite phases. We find that teleportation from a single-rail single-photon qubit to a coherent-state qubit is better than the opposite direction in terms of fidelity and success probability. We compare our results with those using a different type of hybrid entanglement between a polarized single-photon qubit and a coherent state.     

Inertial effects on cylindrical particle migration in linear shear flow near a wall

Micro-/nanoparticle-based systems are regarded as one of the possible candidates due to the engineerability and multifunctionality to maximize the accumulation of the nano-/microparticle-based drug delivery system on the target. Recent advances in nanotechnology enable the fabrication of diverse particle shapes from simple spherical particles to more complex shapes. The particle dynamics in blood flow and endocytosis characteristics of non-spherical particles change as the non-sphericity effect increases. We used a numerical approach to investigate the particle dynamics in linear shear flow near a wall. We examined the dynamics of slender cylindrical particles with aspect ratio γ = 5.0 in terms of particle trajectory, velocity, and force variation for different Stokes numbers over time. We identified the rotating inertia of particle near a wall as the source of inertial migration toward the wall. The drift velocity of slender cylindrical particles is comparable to that of discoidal particles. We discuss the possibilities and limitations of using slender cylindrical particles as a drug delivery system.     

Nonparametric approach for uncertainty-based multidisciplinary design optimization considering limited data

Uncertainty-based multidisciplinary design optimization (UMDO) has been widely acknowledged as an advanced methodology to address competing objectives and reliable constraints of complex systems by coupling relationship of disciplines involved in the system. UMDO process consists of three parts. Two parts are to define the system with uncertainty and to formulate the design optimization problem. The third part is to quantitatively analyze the uncertainty of the system output considering the uncertainty propagation in the multidiscipline analysis. One of the major issues in the UMDO research is that the uncertainty propagation makes uncertainty analysis difficult in the complex system. The conventional methods are based on the parametric approach could possibly cause the error when the parametric approach has ill-estimated distribution because data is often insufficient or limited. Therefore, it is required to develop a nonparametric approach to directly use data. In this work, the nonparametric approach for uncertainty-based multidisciplinary design optimization considering limited data is proposed. To handle limited data, three processes are also adopted. To verify the performance of the proposed method, mathematical and engineering examples are illustrated.