On the Security Bootstrapping in Named Data Networking

By requiring all data packets been cryptographically authenticatable, the Named Data Networking (NDN) architecture design provides a basic building block for secured networking. This basic NDN function requires that all entities in an NDN network go through a security bootstrapping process to obtain the initial security credentials. Recent years have witnessed a number of proposed solutions for NDN security bootstrapping protocols. Built upon the existing results, in this paper we take the next step to develop a systematic model of security bootstrapping: Trust-domain Entity Bootstrapping (TEB). This model is based on the emerging concept of trust domain and describes the steps and their dependencies in the bootstrapping process. We evaluate the expressiveness and sufficiency of this model by using it to describe several current bootstrapping protocols

A Novel Compact Quadruple-Band Indoor Base Station Antenna for 2G/3G/4G/5G Systems

This paper presents a quadruple-band indoor base station antenna for 2G/3G/4G/5G mobile communications, which covers multiple frequency bands of 0.8 - 0.96 GHz, 1.7 - 2.7 GHz, 3.3 - 3.8 GHz and 4.8 - 5.8 GHz and has a compact size with its overall dimensions of 204 × 175 × 39 mm 3 . The lower frequency bands over 0.8 - 0.96 GHz and 1.7 - 2.7 GHz are achieved through the combination of an asymmetrical dipole antenna and parasitic patches. A stepped-impedance feeding structure is used to improve the impedance matching of the dipole antenna over these two frequency bands. Meanwhile, the feeding structure also introduces an extra resonant frequency band of 3.3 - 3.8 GHz. By adding an additional small T-shaped patch, the higher resonant frequency band at 5 GHz is obtained. The parallel surrogate model-assisted hybrid differential evolution for antenna optimization (PSADEA) is employed to optimize the overall quadruple-band performance. We have fabricated and tested the final optimized antenna whose average gain is about 5.4 dBi at 0.8 - 0.96 GHz, 8.1 dBi at 1.7 - 2.7 GHz, 8.5 dBi at 3.3 - 3.8 GHz and 8.1 dBi at 4.8 - 5.0 GHz respectively. The proposed antenna has high efficiency and is of low cost and low profile, which makes it an excellent candidate for 2G/3G/4G/5G base station antenna systems

HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video

We introduce HOSNeRF, a novel 360{\deg} free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video. Our method enables pausing the video at any frame and rendering all scene details (dynamic humans, objects, and backgrounds) from arbitrary viewpoints. The first challenge in this task is the complex object motions in human-object interactions, which we tackle by introducing the new object bones into the conventional human skeleton hierarchy to effectively estimate large object deformations in our dynamic human-object model. The second challenge is that humans interact with different objects at different times, for which we introduce two new learnable object state embeddings that can be used as conditions for learning our human-object representation and scene representation, respectively. Extensive experiments show that HOSNeRF significantly outperforms SOTA approaches on two challenging datasets by a large margin of 40% ~ 50% in terms of LPIPS. The code, data, and compelling examples of 360{\deg} free-viewpoint renderings from single videos will be released in https://showlab.github.io/HOSNeRF.Comment: Project page: https://showlab.github.io/HOSNeR