Spectral characteristics of tapered LPG device as a sensing element for refractive index and temperature

The fabrication and characterization of long-period gratings (LPGs) in fiber tapers is presented alongside supporting theory. The devices possess a high sensitivity to the index of aqueous solutions due to an observed spectral bifurcation effect, yielding a limiting index resolution of ±8.5×10-5 for solutions with an index in the range 1.330-1.335.

Spectral characteristics of tapered LPG device as a sensing element for refractive index and temperature

The fabrication and characterization of long-period gratings (LPGs) in fiber tapers is presented alongside supporting theory. The devices possess a high sensitivity to the index of aqueous solutions due to an observed spectral bifurcation effect, yielding a limiting index resolution of ±8.5 × 10-5 for solutions with an index in the range 1.330-1.335. © 2006 IEEE.

Tapered fibre LPG device as a sensing element for refractive index

The fabrication and characterisation of Long Period Gratings in fibre tapers is presented alongside supporting theory. The devices possess a high sensitivity to the index of aqueous solutions due to an observed spectral bifurcation effect.

Matching theory based travel plan aware charging algorithms in V2G smart grid networks

The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.