This paper reports a dual-polarized graphene-based multi-functional device which could switch between rasorber and absorber flexibly. The only difference between rasorber and absorber is that rasorber has a transmission window with low loss. Therefore, a wideband absorber is proposed at the first step. Then, four split-ring resonators (SRRs) are introduced to the absorber, which makes the electromagnetic (EM) energy could be reflected at the certain frequency band. The state (on/off) of SRRs and absorber can be controlled by the chemical potential of graphene. To find a new pathway for this part of the reflected energy, metal ground of the absorber is replaced by a reconfigurable graphene-based FSS. The proposed FSS could be switched between FSS and metal plate by controlling the chemical potential of graphene ring embedded in the bottom metal layer. Therefore, the proposed multi-functional device could be obtained by combing the absorber with SRRs and reconfigurable FSS. When the proposed device serves as a rasorber, it has an absorption-transmission-absorption response with superior selectivity. When it performs as an absorber, it has wideband performance with high absorptive rate. It is an attractive candidate for stealth applications.
There is a growing interest in developing and implementing adaptive instructional systems to improve, automate, and personalize student education. A necessary part of any such adaptive instructional system is a student model used to predict or analyze learner behavior and inform adaptation. To help inform researchers in this area, this paper presents a state-of-theart review of 11 years of research (2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021) in student modeling, focusing on learner characteristics, learning indicators, and foundational aspects of dissimilar models. We mainly emphasize increased prediction accuracy when using multidimensional learner data to create multimodal models in real-world adaptive instructional systems. In addition, we discuss challenges inherent in real-world multimodal modeling, such as uncontrolled data collection environments leading to noisy data and data sync issues. Finally, we reinforce our findings and conclusions through an industry case study of an adaptive instructional system. In our study, we verify that adding multiple data modalities increases our model prediction accuracy from 53.3% to 69%. At the same time, the challenges encountered with our real-world case study, including uncontrolled data collection environment with inevitably noisy data, calls for synchronization and noise control strategies for data quality and usability.
This article presents ultra-short pulse generators based on shaping-differential and phase detect circuits fabricated in a 0.13-lm complementary metal-oxide-semiconductor process. By using a differential circuit, the shapingdifferential and phase detect pulse generators produce pulses with a pulse width of 51.5 and 79.0 ps, respectively. The measured output powers from the shapingdifferential and phase detect pulse generators are 234.6 dBm at 16 GHz, and 228.3 dBm at 8 GHz, respectively.
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