Dynamic Uncertainty:Exploring the Spatial Order of Future Digital Architecture

The spatial order of architecture has been significantly impacted by digital architectural design and production,creating a dynamic uncertainty.This study aims to explore digital architecture from the perspective of spatial order,discussing the antidote/poison effect caused by digital technologies in architectural practice and the cultural digital changes in digital architectures.The study selected four digital architecture cases,including the(W)rapper at Los Angeles by Eric Owen Moss,Beijing Daxing International Airport by Zaha Hadid,3D Print Niaokan Bridge by Xu Weiguo,and World Internet Conference Center by Yuan Feng.This study is hypothesising that the future special order of digital architectures will be a dynamic and balanced new spatial order.This new order includes the symbiosis of a human-machine and virtual-real hierarchy;the interactive co-existence between nature,humanity and technology;and the creative multi-immersive sharing of parametric information,built-environment resources and cultural artistic information.The evolution of spatial order of future digital architecture will be discussed in connection with the idea of the metaverse.The value of this work is its ability to inspire a broader examination of the new order of digital architectural space.

Speckle noise reduction in digital holography with spatial light modulator and nonlocal means algorithm

An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Multiple holograms are reconstructed and superimposed, and the intensity is averaged to smooth the noise. The adaptive algorithm based on the nonlocal means is designed to further suppress the speckle. The presented method is compared with other methods reduction is improved, and the proposed method is effective The experimental results show that speckle and feasible.

Design and Implementation of Spatial Data Watermarking Service System

Nowadays, more and more digitalized spatial data are sold and transmitted on the Internet. Thus, there arises an important issue about copyright protection of the digital data. To solve this problem, this paper has designed and implemented a spatial data watermarking service (SDWS) system which can provide a secure framework for data transaction and transfer via the Internet and protect the rights of both copyright owners and consumers at the same time.

Sampling Designs for Validating Digital Soil Maps: A Review

Sampling design(SD) plays a crucial role in providing reliable input for digital soil mapping(DSM) and increasing its efficiency.Sampling design, with a predetermined sample size and consideration of budget and spatial variability, is a selection procedure for identifying a set of sample locations spread over a geographical space or with a good feature space coverage. A good feature space coverage ensures accurate estimation of regression parameters, while spatial coverage contributes to effective spatial interpolation.First, we review several statistical and geometric SDs that mainly optimize the sampling pattern in a geographical space and illustrate the strengths and weaknesses of these SDs by considering spatial coverage, simplicity, accuracy, and efficiency. Furthermore, Latin hypercube sampling, which obtains a full representation of multivariate distribution in geographical space, is described in detail for its development, improvement, and application. In addition, we discuss the fuzzy k-means sampling, response surface sampling, and Kennard-Stone sampling, which optimize sampling patterns in a feature space. We then discuss some practical applications that are mainly addressed by the conditioned Latin hypercube sampling with the flexibility and feasibility of adding multiple optimization criteria. We also discuss different methods of validation, an important stage of DSM, and conclude that an independent dataset selected from the probability sampling is superior for its free model assumptions. For future work, we recommend: 1) exploring SDs with both good spatial coverage and feature space coverage; 2) uncovering the real impacts of an SD on the integral DSM procedure;and 3) testing the feasibility and contribution of SDs in three-dimensional(3 D) DSM with variability for multiple layers.