Query: space web capture

title: Space Debris Ontology for ADR Capture Methods Selection
abstract: Studies have concluded that active debris removal (ADR) of the existing in orbit mass is necessary. However, the quest for an optimal solution does not have a unique answer and the available data often lacks coherence. To improve this situation, modern knowledge representation techniques, that have been shaping the World Wide Web, medicine and pharmacy, should be employed. Prior efforts in the domain of space debris have only focused onto the space situational awareness, neglecting ADR. To bridge this gap we present a domain ontology of intact derelict objects, i. e. payloads and rocket bodies, for ADR capture methods selection. The ontology is defined on a minimal set of physical, dynamical and statistical parameters of a target object. The practicality and validity of the ontology are demonstrated by applying it onto a database of 30 representative objects, built by combining structured and unstructured data from publicly available sources. The analysis of results proves the ontology capable of inferring the most suited ADR capture methods for considered objects. Furthermore, it confirms its ability to handle the input data from different sources transparently, minimizing user input. The developed ontology provides an initial step towards a more comprehensive knowledge representation framework meant to improve data management and knowledge discovery in the domain of space debris. Furthermore, it provides a tool that should make the initial planning of future ADR missions simpler yet more systematic.

title: Bionic Design and Experimental Study for the Space Flexible Webs Capture System
abstract: In order to make the space flexible webs system have more effective capability of capture, this paper designs a new space debris removal device, which consists of bionic flexible webs, central hub, magnetic mass and rotating mechanism. According to the principle of bionics and institutional design method, which based on the research of spider web structure and capture performance analysis. Firstly, the image processing system of spider web is established, and the spider web image is digitally processed to extract the structure shape of the spider web. According to the structure of spider web, a simplified cobweb like flexible structure is proposed and a "cobweb like" flexible capture device is designed. Then, the model of flexible web is established based on the finite element method, and the capture effect is compared with the traditional quadrilateral webs. Finally, a ground experiment system of "cobweb like" flexible capture device is designed, and a verification experiment of the capture effect of the flexible webs is carried out. The results show that the bionic design scheme in this paper can fully meet the design requirements for the flexible webs capture system in space and the research provides theoretical and experimental references for the engineering realization of the space flexible webs capture system.

title: Where to go and what to do: Extracting leisure activity potentials from Web data on urban space
abstract: Web data is the most prominent source of information for deciding where to go and what to do. Exploiting this source for geographic analysis, however, does not come without difficulties. First, in recent years, the amount and diversity of available Web information about urban space have exploded, and it is therefore increasingly difficult to overview and exploit. Second, the bulk of information is in an unstructured form which is difficult to process and interpret by computers. Third, semi structured sources, such as Web rankings, geolocated tags, check ins, or mobile sensor data, do not fully reflect the more subtle qualities of a place, including the particular functions that make it attractive. In this article, we explore a method to capture leisure activity potentials from Web data on urban space using semantic topic models. We test three supervised multi label machine learning strategies exploiting geolocated webtexts and place tags to estimate whether a given type of leisure activity is afforded or not. We train and validate these models on a manually curated dataset labeled with leisure ontology classes for the city of Zwolle, and discuss their potential for urban leisure and tourism research and related city policies and planning. We found that multi label affordance estimation is not straightforward but can be made to work using both official webtexts and user generated content on a medium semantic level. This opens up new opportunities for data driven approaches to urban leisure and tourism studies.

title: Combining Web Audio Streaming, Motion Capture, and Binaural Audio in a Telepresence System
abstract: This paper describes the use of spatialized binaural 3D audio in the Digiscape telepresence system. Digiscape is a custom built system that enables groups of users of visualization platforms, including CAVEs and wall sized displays, to collaborate at a distance while visualizing and manipulating large and complex data sets. Digiscape supports web based audio and video streaming as well as data sharing among its constituent platforms. Using motion capture systems, the locations of collaborators in each physical spaces are sent to the remote platforms, which spatialize the collaborators' audio streams in their local audio space. The audio spaces can be configured in a variety of ways, from a single shared audio space to mapped, adjacent, contained, split, or distorted audio spaces, facilitating the exploration of the possibilities of spatialized voice communication in telepresence systems.

title: Fine structural analysis on triad spinning spigots of an orb web spider's capture threads
abstract: Capture threads of the golden orb web spider Nephila clavata are produced from the silks of a pair of triad spinning units composed of a flagelliform gland (FLG) and two aggregate glands (AGG) In N. clavata, arrangement of the triad spigots is closely related to coating an axial supporting fiber with sticky aqueous droplets on a continuous and consistent basis for capture thread production. The central spigot of FLG and peripherally located AGG spigots are aligned along a single plane, and both have bullet type spigots with flexible segments. In particular, the pear shaped spigot of the AGG with a wide aperture nozzle provides not only sufficient luminal space for controlling transient storage of the aqueous gluey substance but also an effective spatial system that thoroughly coats the axial fibers with a viscous aqueous solution.

title: Next generation consumer innovation search: Identifying early stage need solution pairs on the web
abstract: All innovations consist of a need paired with a responsive solution a need solution pair (von Hippel and von Krogh 2016) Today, technical advances in machine learning techniques for natural language understanding, such as semantic word space models and semantic network analytics, have made it practical to capture descriptions of early stage, need solution pairs mentioned anywhere in the open, textual content of the Internet. Producers and anyone can now thus look for user innovations posted on the web that may involve either known or newly defined needs coupled to new solutions that are gaining traction. This is important because, as is now understood, users, rather than producers, tend to pioneer functionally new products and services for which both the need and the solution may be novel. In this paper, we demonstrate via a case study both the practicality and the value of searching for early stage need solution pairs via machine learning methods and assessing the likely general interest in each usergenerated innovation by also identifying the trends in posting and query frequencies related to it. The new need solution pair search method we describe and test here can, we claim, serve as a very valuable complement to traditional market research techniques and practices.

title: Nonlinear 3D cosmic web simulation with heavy tailed generative adversarial networks
abstract: Fast and accurate simulations of the non linear evolution of the cosmic density field are a major component of many cosmological analyses, but the computational time and storage required to run them can be exceedingly large. For this reason, we use generative adversarial networks (GANs) to learn a compressed representation of the 3D matter density field that is fast and easy to sample, and for the first time show that GANs are capable of generating samples at the level of accuracy of other conventional methods. Using sub volumes from a suite of GADGET 2 N body simulations, we demonstrate that a deep convolutional GAN can generate samples that capture both large and small scale features of the matter density field, as validated through a variety of n point statistics. The use of a data scaling that preserves high density features and a heavy tailed latent space prior allow us to obtain state of the art results for fast 3D cosmic web generation. In particular, the mean power spectra from generated samples agree to within 5% up to k=3 and within 10% for k<5 when compared with N body simulations, and similar accuracy is obtained for a variety of bispectra. By modeling the latent space with a heavy tailed prior rather than a standard Gaussian, we better capture sample variance in the high density voxel PDF and reduce errors in power spectrum and bispectrum covariance on all scales. Furthermore, we show that a conditional GAN can smoothly interpolate between samples conditioned on redshift. Deep generative models, such as the ones described in this work, provide great promise as fast, low memory, high fidelity forward models of large scale structure.

title: bi HPTM: An Effective Semantic Matchmaking Model for Web Service Discovery
abstract: Analyzing textual semantics in matching user query and service description is critical for Web service discovery. Existing works mostly extract the features of the description and query independently, downgrading them into word level calculation, which can not jointly extract the accurate semantics. For this issue, this work explores a way to enable the semantic matching for the contents (including words, phrases, or sentences) in query and the sentences in service description, by mapping words and sentences into the same semantic space. Specifically, we propose an unsupervised Bayesian probabilistic model, bi Directional Hybrid Priors Topic Model (bi HPTM) to capture the textual semantics of the words and sentences in a probabilistic simplex, which provides a flexible operation to build the semantic links from the queries to service descriptions. Meanwhile, the textual semantics generated by bi HPTM is highly interpretable that help to understand the user requirements. The proposed model is examined by ProgrammableWeb. Experimental results demonstrate that bi HPTM outperforms state of the art methods for semantic service discovery on service classification and retrieval. The visualizations of the nearest neighbored queries and descriptions show the insights of our model on capturing the latent semantics of Web services.

title: MinoanER: Schema Agnostic, Non Iterative, Massively Parallel Resolution of Web Entities
abstract: Entity Resolution (ER) aims to identify different descriptions in various Knowledge Bases (KBs) that refer to the same entity. ER is challenged by the Variety, Volume and Veracity of entity descriptions published in the Web of Data. To address them, we propose the MinoanER framework that simultaneously fulfills full automation, support of highly heterogeneous entities, and massive parallelization of the ER process. MinoanER leverages a token based similarity of entities to define a new metric that derives the similarity of neighboring entities from the most important relations, as they are indicated only by statistics. A composite blocking method is employed to capture different sources of matching evidence from the content, neighbors, or names of entities. The search space of candidate pairs for comparison is compactly abstracted by a novel disjunctive blocking graph and processed by a non iterative, massively parallel matching algorithm that consists of four generic, schema agnostic matching rules that are quite robust with respect to their internal configuration. We demonstrate that the effectiveness of MinoanER is comparable to existing ER tools over real KBs exhibiting low Variety, but it outperforms them significantly when matching KBs with high Variety.

title: ACCESS AND WEB SHARING OF 3D DIGITAL DOCUMENTATION OF ENVIRONMENTAL AND ARCHITECTURAL HERITAGE
abstract: The techniques and methods to capture and represent in a three dimensional digital space the shape of objects belonging to Cultural Heritage have become more widespread, regarding both the economic and practical accessibility of technologies and equipment. At the same time, systems and tools have developed to integrate different 3D survey techniques that allow to achievement a complete acquisition of the tangible assets, considering the purposes of the survey, the required accuracy and the representation scale. The product of an integrated (image based and range base acquisition) and multi scale (architectural and landscape scale) digital survey is a metric 3D reconstruction, potentially suitable for a broader 'use' and 'user' and not only for visualisation and documentation. According to this vision, the 3D model becomes a container of information, which include different type of data depending on the users and the aim of the work. The final result of this process can be the valorisation of the Cultural Heritage and its environment, through the access from experts and non experts users. The aim of the article is showing the entire pipeline for 3D measurement, survey data acquisition, modelling, and representation of tangible assets and the related layers of information, as "best practice" to improve the Cultural Heritage knowledge, fruition, and sharing.