Electromagnetic field sensors are widely used in various areas. In recent years, great progress has been made in the optical sensing technique for electromagnetic field measurement, and varieties of corresponding sensors have been proposed. Types of magnetic field optical sensors were presented, including probes-based Faraday effect, magnetostrictive materials, and magnetic fluid. The sensing system-based Faraday effect is complex, and the sensors are mostly used in intensive magnetic field measurement. Magnetic field optical sensors based on magnetic fluid have high sensitivity compared to that based on magnetostrictive materials. Three types of electric field optical sensors are presented, including the sensor probes based on electric-optic crystal, piezoelectric materials, and electrostatic attraction. The majority of sensors are developed using the sensing scheme of combining the LiNbO3 crystal and optical fiber interferometer due to the good electro-optic properties of the crystal. The piezoelectric materials-based electric field sensors have simple structure and easy fabrication, but it is not suitable for weak electric field measurement. The sensing principle based on electrostatic attraction is less commonly-used sensing methods. This review aims at presenting the advances in optical sensing technology for electromagnetic field measurement, analyzing the principles of different types of sensors and discussing each advantage and disadvantage, as well as the future outlook on the performance improvement of sensors.
The most popular strategies for dealing with packet collisions at the Medium Access Control (MAC) layer in distributed wireless networks use a combination of carrier sensing and collision avoidance. When the collision avoidance strategy fails, such schemes cannot detect collisions and corrupted data frames are still transmitted in their entirety, thereby wasting the channel bandwidth and significantly reducing the network throughput. To address this problem, this paper proposes a new wireless MAC protocol capable of collision detection. The basic idea of the proposed protocol is the use of pulses in an out-of-band control channel for exploring channel condition and medium reservation and achieving both collision avoidance and collision detection. The performance of the proposed MAC protocol has been investigated using extensive analysis and simulations. Our results show that, as compared with existing MAC protocols, the proposed protocol has significant performance gains in terms of node throughput. Additionally, the proposed protocol is fully distributed and requires no time synchronization among nodes.
Most research on working memory (WM) training for children with developmental dyslexia (DD) has focused on western alphabetical languages. Moreover, most of these studies used a combination of training tasks targeting a variety of WM components, making it difficult to determine whether WM training generates a general improvement in overall reading, or improves specific cognitive skills corresponding to the WM components that are targeted in training. We tested the general and specific effects of WM training on the reading skills of 45 Chinese children with DD, grades 3 to 5. In Experiment 1, the experimental group received a program targeting the verbal WM component; in Experiment 2, the experimental group was trained with a program targeting visuospatial WM. In both experiments the control group played a placebo video game. In Experiment 1, the experimental group outperformed the control group on the visual rhyming task, which is highly correlated with verbal WM. In Experiment 2, the experimental group outperformed the control group on the orthographic awareness test, which is highly correlated with visuospatial WM. Furthermore, in both Experiment 1 and Experiment 2, the experimental groups outperformed the control groups on the fast word naming test, which is highly related to both visuospatial WM and verbal WM. Results indicated that WM training improved specific reading-related cognitive skills that are highly correlated with the specific WM components that were the target of training.
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