Three Types of Reading Class in Primary Chinese Teaching

Under the new curriculum concept, Chinese reading class should contain three forms, namely single-text intensive reading teaching, multi-text skimming teaching and whole book reading teaching. Despite different tasks as well as strategies in each form, the three forms are inseparably interconnected and integrated at three levels of topic learning and make up the whole process of reading teaching experience

Systematic Review of the Use of Multiperson Activity Schedules for Individuals With Disabilities

Multiperson activity schedules capitalize on the benefits of independent activity schedules, a commonly used visual support for individuals with disabilities. Activity schedules minimize the need for adult prompting and increase independence with complex tasks by breaking them down into pictures, written words, or videos. Multiperson schedules allow pairs and small groups of individuals with disabilities to work together with minimal adult involvement to accomplish a task. This systematic review aims to inform researchers and other interested persons regarding the use of multiperson activity schedules to aid in decision-making and support implementation. We screened 146 articles and dissertations against our study inclusion criteria and found 11 studies meeting the criteria. Data compiled from the 11 studies highlight the usefulness and effectiveness of this evolving intervention. Strengths and weaknesses of the included studies are discussed, as well as implications for future research and practice

Power Efficient Visible Light Communication (VLC) with Unmanned Aerial Vehicles (UAVs)

A novel approach that combines visible light communication (VLC) with unmanned aerial vehicles (UAVs) to simultaneously provide flexible communication and illumination is proposed. To minimize the power consumption, the locations of UAVs and the cell associations are optimized under illumination and communication constraints. An efficient sub-optimal solution that divides the original problem into two sub-problems is proposed. The first sub-problem is modeled as a classical smallest enclosing disk problem to obtain the optimal locations of UAVs, given the cell association. Then, assuming fixed UAV locations, the second sub-problem is modeled as a min-size clustering problem to obtain the optimized cell association. In addition, the obtained UAV locations and cell associations are iteratively optimized multiple times to reduce the power consumption. Numerical results show that the proposed approach can reduce the total transmit power consumption by at least 53.8% compared to two baseline algorithms with fixed UAV locations.Comment: 4 pages, 4 figures. Accepted for publication in IEEE Communications Letter

The Spatial Dimming Scheme for the MU-MIMO-OFDM VLC System

Multiuser visible light communication (MU-VLC) systems utilizing multiple-input multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) are gaining increased attentions recently. Visible light communication (VLC) links are expected to work under different illumination conditions and, thus, the need for dimming control mechanisms. However, the traditional analog- and digital-based dimming schemes have adverse effects on the data communications performance, such as clipping distortion and the variation of the duty cycle. In this paper, spatial dimming schemes based on the zero-forcing and the minimum mean-squared error precoding schemes are proposed for direct-current biased optical OFDM based indoor MU-MIMO VLC system, and the bipolar optical OFDM signal is biased by a fixed dc level. Transmit antenna selection algorithms are designed for the optimum working light emitting diodes (LEDs) subset at each dimming level. Owing to the simultaneously exploration of the selection diversity of LEDs-based lights and the channel state information, the proposed spatial dimming schemes outperform the traditional dimming schemes, which is also verified by simulation results. Thus, the proposed schemes are shown to have a great potential to be applied in practical MU-MIMO-OFDM VLC systems

Exploiting Visual Semantic Reasoning for Video-Text Retrieval

Video retrieval is a challenging research topic bridging the vision and language areas and has attracted broad attention in recent years. Previous works have been devoted to representing videos by directly encoding from frame-level features. In fact, videos consist of various and abundant semantic relations to which existing methods pay less attention. To address this issue, we propose a Visual Semantic Enhanced Reasoning Network (ViSERN) to exploit reasoning between frame regions. Specifically, we consider frame regions as vertices and construct a fully-connected semantic correlation graph. Then, we perform reasoning by novel random walk rule-based graph convolutional networks to generate region features involved with semantic relations. With the benefit of reasoning, semantic interactions between regions are considered, while the impact of redundancy is suppressed. Finally, the region features are aggregated to form frame-level features for further encoding to measure video-text similarity. Extensive experiments on two public benchmark datasets validate the effectiveness of our method by achieving state-of-the-art performance due to the powerful semantic reasoning.Comment: Accepted by IJCAI 2020. SOLE copyright holder is IJCAI (International Joint Conferences on Artificial Intelligence), all rights reserved. http://static.ijcai.org/2020-accepted_papers.htm