Energy storage is a key requirement for the emerging wearable technologies. Recent progress in this direction includes the development of fiber based batteries and capacitors and even some examples of such fibers incorporated into prototype textiles. Herein we discuss the advantages of using the wet-spinning process to create nanostructured carbon based materials as wearable energy storage. The ability to control the physical, mechanical, electrical, and electrochemical properties of carbon nanotube based fibers holds great promise to develop smart polymeric structure as an energy storing materials including fibers and textiles. This is the first comprehensive review to discuss effect of nanostructured energy materials on the electrochemical properties of carbon nanotube based fibers which covers the various compositions, spinning and fabrication conditions on the performance of wearable energy storage.

This paper concerns uplink grant-free nonorthogonal multiple access, where the handshaking procedure is not required to reduce control signaling overhead and transmission latency. In especially the dynamic scenarios, e.g., Internet of vehicles, the active users have to be identified and their channel state information needs to be estimated before performing multiuser detection. We investigate the joint user activity detection (UAD) and channel estimation (CE), which provides necessary information for data detection. In this paper, the joint UAD and CE is formulated as a block sparse signal recovery problem. First, the block orthogonal matching pursuit (BOMP) algorithm is studied for this problem, but its complexity grows with the fourth power of active user number, which hinders its application. Then, block sparse Bayesian learning (BSBL) is investigated to solve this problem, and in particular a low complexity message passing based implementation of BSBL with belief propagation and mean field is developed. The proposed message passing based BSBL (MP-BSBL) algorithm has a complexity independent of active user number, which can be significantly lower than that of the BOMP algorithm. In addition, MP-BSBL provides an estimate of the noise power, which can be readily used for data detection. Simulation results show that the MP-BSBL algorithm delivers almost the same performance as BOMP with the exact knowledge of active user number and can reach the performance bound for channel estimation.

Approaches that are, to our knowledge, novel, are proposed in this paper to improve the accuracy performance of self-mixing interferometry (SMI) for displacement measurement. First, the characteristics associated with signals observed in SMI systems are studied, based on which a new procedure is proposed for achieving accurate estimation of the laser phase. The studies also revealed the reasons for the inherent errors associated with the existing SMI-based techniques for displacement measurement. Then, this paper presents a new method for estimating the optical feedback level factor (denoted by C) in real time. Combining the new algorithms for estimating the laser phase and updating C value, the paper finally presents a novel technique for displacement measurement with improved accuracy performance in contrast to existing techniques. The proposed technique is verified by both simulation and experimental data.

When phase shifting profilometry (PSP) is employed for 3-D shape measurement, the object must be kept static during the projection and acquisition of the multiple fringe patterns. Errors will occur when the object moves and if the projection and capture of fringe patterns are not fast enough. In this paper, a new approach is proposed to tackle the problem, consisting of two steps. Firstly, the rotation matrix and translation vector describing the movement of the object are estimated using a set of marks placing on the surface of the object. Then the expressions of the fringe patterns under the influence of 2-D object movement are derived, which are employed to determine the correct phase map, leading to accurate measurement of the profile. Simulations and experiments are presented to verify the effectiveness of the proposed algorithm.

Phase unwrapping is an important and challenging issue in fringe pattern profilometry. In this Letter we propose an approach to recover absolute phase maps of two fringe patterns with selected frequencies. Compared to existing temporal multiple frequency algorithms, the two frequencies in our proposed algorithm can be high enough and thus enable efficient and accurate recovery of absolute phase maps. Experiment results are presented to confirm the effectiveness of the proposed technique.