A novel 3D RRAM concept using a stackable multi-layer 1TXR memory cell structure is proposed. The access transistor is fabricated in silicon, which has excellent affinity to the standard CMOS process. Using an 8-layer metal of stacked 1TXR (X=64) as an example, the density is over 260% higher than that of the conventional single layer 1T1R structure. Further, a corresponding operation algorithm is put forward, which can inhibit effectively mis-write and mis-read caused by sneaking current and reduce power consumption.

Inter-satellite link (ISL) is an important part of the next generation global navigation satellite system (GNSS). In this paper, key technologies of GNSS ISL ranging and time synchronization are researched. Considering that Ka frequency band is used for ISL, a fixed topology is designed and a new time division duplex (TDD) mode is proposed after analyzing the characteristics of GNSS constellations. A novel method called Non-coherent Dual One-way Measuring (NC-DOWM) is applied to this TDD mode. In addition, relevant mathematical formulas, error models and error compensation are discussed in detail. It is found that the proposed NC-DOWM method for GNSS ISL ranging and time synchronization outperforms the current method for GPS in terms of channel utilization efficiency and measuring precision. Furthermore, the presented method has excellent anti-interference capability and engineering feasibility, which can provide a strong technical support for the ISL of the next generation GNSS.

A generative model is presented for two types of person image generation in this paper. First, this model is applied to pose-guided person image generation, i.e., converting the pose of a source person image to the target pose while preserving the texture of that source person image. Second, this model is also used for clothing-guided person image generation, i.e., changing the clothing texture of a source person image to the desired clothing texture. The core idea of the proposed model is to establish the multi-scale correspondence, which can effectively address the misalignment introduced by transferring pose, thereby preserving richer information on appearance. Specifically, the proposed model consists of two stages: 1) It first generates the target semantic map imposed on the target pose to provide more accurate guidance during the generation process. 2) After obtaining the multi-scale feature map by the encoder, the multi-scale correspondence is established, which is useful for a fine-grained generation. Experimental results show the proposed method is superior to state-of-the-art methods in pose-guided person image generation and show its effectiveness in clothing-guided person image generation.

We describe attempts to have robots behave as embodied knowledge media that will permit knowledge to be communicated through embodied interactions in the real world. The key issue here is to give robots the ability to associate interactions with information content while interacting with a communication partner. Toward this end, we present two contributions in this paper. The first concerns the formation and maintenance of joint intention, which is needed to sustain the communication of knowledge between humans and robots. We describe an architecture consisting of multiple layers that enables interaction with people at different speeds. We propose the use of an affordance-based method for fast interactions. For medium-speed interactions, we propose basing control on an entrainment mechanism. For slow interactions, we propose employing defeasible interaction patterns based on probabilistic reasoning. The second contribution is concerned with the design and implementation of a robot that can listen to a human instructor to elicit knowledge, and present the content of this knowledge to a person who needs it in an appropriate situation. In addition, we discuss future research agenda toward achieving robots serving as embodied knowledge media, and fit the robots-as-embodied-knowledge-media view in a larger perspective of Conversational Informatics.