Semantically interoperable three-dimensional scientific objects

2012 ◽  
Vol 27 (1) ◽  
pp. 33-55
Author(s):  
Marios Pitikakis ◽  
Manolis Vavalis ◽  
Catherine Houstis
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Digital Content ◽  
Management Systems ◽  
Formal Approach ◽  
Knowledge Based ◽  
Shape Models ◽  
On Line ◽  
Scientific Objects ◽  
Search And Retrieval

AbstractIn recent years, digital content of three-dimensional (3D) scientific objects has become widespread and is made available in a plethora of on-line scientific repositories. A systematic and formal approach becomes necessary to represent the knowledge/information related to these objects, in order to facilitate their search, retrieval and reuse. In this paper, we employ semantic interoperability to manage 3D scientific object content in a large-scale framework of scientific applications that consists of 3D shape models, associated tools and resources. We use an advanced ontological organization for their metadata, powerful reasoning engines for their search and retrieval and we elucidate several crucial issues in the design and implementation of 3D knowledge-based management systems.

scholarly journals Automated Localization and Classification of Expressway Pole-Like Road Facilities from Mobile Laser Scanning Data

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Tran Thanh Ha ◽  
Taweep Chaisomphob
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Advanced Technology ◽  
Promising Alternative ◽  
Knowledge Based ◽  
Road Mapping ◽  
Vertical Height

Mobile LiDAR is an emerging advanced technology for capturing three-dimensional road information at a large scale effectively and precisely. Pole-like road facilities are crucial street infrastructures as they provide valuable information for road mapping and road inventory. Thus, the automated localization and classification of road facilities are necessary. This paper proposes a voxel-based method to detect and classify pole-like objects in an expressway environment based on the spatially independent and vertical height continuity analysis. First, the ground points are eliminated, and the nonground points are merged into clusters. Second, the pole-like objects are extracted using horizontal cross section analysis and minimum vertical height criteria. Finally, a set of knowledge-based rules, which comprise height features and geometric shape, is constructed to classify the detected road poles into different types of road facilities. Two test sites of point clouds in an expressway environment, which are located in Bangkok, Thailand, are used to assess the proposed method. The proposed method extracts the pole-like road facilities from two datasets with a detection rate of 95.1% and 93.5% and an overall quality of 89.7% and 98.0% in the classification stage, respectively. This shows that the algorithm could be a promising alternative for the localization and classification of pole-like road facilities with acceptable accuracy.

scholarly journals Variable Selection and Grouping in a Paper Machine Application

2007 ◽  
Vol 2 (2) ◽  
pp. 111 ◽  
Author(s):  
Timo Ahola ◽  
Esko Juuso ◽  
Kauko Leiviskä
Keyword(s):  
Variable Selection ◽  
Large Scale ◽  
Expert Knowledge ◽  
Paper Mill ◽  
Case Based Reasoning ◽  
Paper Machine ◽  
Knowledge Based ◽  
New Information ◽  
On Line ◽  
The Web

This paper describes the possibilities of variable selection in large-scale industrial systems. It introduces knowledge-based, data-based and model-based methods for this purpose. As an example, Case-Based Reasoning application for the evaluation of the web break sensitivity in a paper machine is introduced. The application uses Linguistic Equations approach and basic Fuzzy Logic. The indicator combines the information of on-line measurements with expert knowledge and provides a continuous indication of the break sensitivity. The web break sensitivity defines the current operating situation at the paper mill and gives new information to the operators. Together with information of the most important variables this prediction gives operators enough time to react to the changing operating situation.

scholarly journals Covering complete proteomes with X-ray structures: a current snapshot

2014 ◽  
Vol 70 (11) ◽  
pp. 2781-2793 ◽  
Author(s):  
Marcin J. Mizianty ◽  
Xiao Fan ◽  
Jing Yan ◽  
Eric Chalmers ◽  
Christopher Woloschuk ◽  
...  
Keyword(s):  
Homology Modeling ◽  
Structure Determination ◽  
Large Scale ◽  
Structural Model ◽  
Target Selection ◽  
Three Dimensional ◽  
X Ray ◽  
X Ray Crystallography ◽  
Knowledge Based ◽  
Wide Range

Structural genomics programs have developed and applied structure-determination pipelines to a wide range of protein targets, facilitating the visualization of macromolecular interactions and the understanding of their molecular and biochemical functions. The fundamental question of whether three-dimensional structures of all proteins and all functional annotations can be determined using X-ray crystallography is investigated. A first-of-its-kind large-scale analysis of crystallization propensity for all proteins encoded in 1953 fully sequenced genomes was performed. It is shown that current X-ray crystallographic knowhow combined with homology modeling can provide structures for 25% of modeling families (protein clusters for which structural models can be obtained through homology modeling), with at least one structural model produced for each Gene Ontology functional annotation. The coverage varies between superkingdoms, with 19% for eukaryotes, 35% for bacteria and 49% for archaea, and with those of viruses following the coverage values of their hosts. It is shown that the crystallization propensities of proteomes from the taxonomic superkingdoms are distinct. The use of knowledge-based target selection is shown to substantially increase the ability to produce X-ray structures. It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined.

Design and calibration of an IVEM for general 3-dimensional imaging of non-diffracting materials

1992 ◽  
Vol 50 (2) ◽  
pp. 1040-1041
Author(s):  
Neil Rowlands ◽  
Jeff Price ◽  
Michael Kersker ◽  
Seichi Suzuki ◽  
Steve Young ◽  
...  
Keyword(s):  
3D Imaging ◽  
Tomographic Reconstruction ◽  
Three Dimensional ◽  
3 Dimensional ◽  
3D Microstructure ◽  
Image Translation ◽  
Digital Correlation ◽  
On Line ◽  
Mechanical Stage ◽  
Projection Angle

Three-dimensional (3D) microstructure visualization on the electron microscope requires that the sample be tilted to different positions to collect a series of projections. This tilting should be performed rapidly for on-line stereo viewing and precisely for off-line tomographic reconstruction. Usually a projection series is collected using mechanical stage tilt alone. The stereo pairs must be viewed off-line and the 60 to 120 tomographic projections must be aligned with fiduciary markers or digital correlation methods. The delay in viewing stereo pairs and the alignment problems in tomographic reconstruction could be eliminated or improved by tilting the beam if such tilt could be accomplished without image translation.A microscope capable of beam tilt with simultaneous image shift to eliminate tilt-induced translation has been investigated for 3D imaging of thick (1 μm) biologic specimens. By tilting the beam above and through the specimen and bringing it back below the specimen, a brightfield image with a projection angle corresponding to the beam tilt angle can be recorded (Fig. 1a).

A Drug Target Interaction Prediction Based on LINE-RF Learning

2020 ◽  
Vol 15 (7) ◽  
pp. 750-757
Author(s):  
Jihong Wang ◽  
Yue Shi ◽  
Xiaodan Wang ◽  
Huiyou Chang
Keyword(s):  
Network Topology ◽  
Drug Target ◽  
Large Scale ◽  
Representation Learning ◽  
New Drugs ◽  
Combination Method ◽  
Learning Methods ◽  
Network Representation ◽  
On Line ◽  
Clinical Experiments

Background: At present, using computer methods to predict drug-target interactions (DTIs) is a very important step in the discovery of new drugs and drug relocation processes. The potential DTIs identified by machine learning methods can provide guidance in biochemical or clinical experiments. Objective: The goal of this article is to combine the latest network representation learning methods for drug-target prediction research, improve model prediction capabilities, and promote new drug development. Methods: We use large-scale information network embedding (LINE) method to extract network topology features of drugs, targets, diseases, etc., integrate features obtained from heterogeneous networks, construct binary classification samples, and use random forest (RF) method to predict DTIs. Results: The experiments in this paper compare the common classifiers of RF, LR, and SVM, as well as the typical network representation learning methods of LINE, Node2Vec, and DeepWalk. It can be seen that the combined method LINE-RF achieves the best results, reaching an AUC of 0.9349 and an AUPR of 0.9016. Conclusion: The learning method based on LINE network can effectively learn drugs, targets, diseases and other hidden features from the network topology. The combination of features learned through multiple networks can enhance the expression ability. RF is an effective method of supervised learning. Therefore, the Line-RF combination method is a widely applicable method.

scholarly journals A Review on Additive Manufacturing Possibilities for Electrical Machines

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1940
Author(s):  
Muhammad Usman Naseer ◽  
Ants Kallaste ◽  
Bilal Asad ◽  
Toomas Vaimann ◽  
Anton Rassõlkin
Keyword(s):  
Additive Manufacturing ◽  
Large Scale ◽  
Three Dimensional ◽  
Electrical Machines ◽  
Electromagnetic Properties ◽  
Scale Production ◽  
Performance Parameters ◽  
Large Scale Production ◽  
One Step ◽  
Manufacturing Techniques

This paper presents current research trends and prospects of utilizing additive manufacturing (AM) techniques to manufacture electrical machines. Modern-day machine applications require extraordinary performance parameters such as high power-density, integrated functionalities, improved thermal, mechanical & electromagnetic properties. AM offers a higher degree of design flexibility to achieve these performance parameters, which is impossible to realize through conventional manufacturing techniques. AM has a lot to offer in every aspect of machine fabrication, such that from size/weight reduction to the realization of complex geometric designs. However, some practical limitations of existing AM techniques restrict their utilization in large scale production industry. The introduction of three-dimensional asymmetry in machine design is an aspect that can be exploited most with the prevalent level of research in AM. In order to take one step further towards the enablement of large-scale production of AM-built electrical machines, this paper also discusses some machine types which can best utilize existing developments in the field of AM.

scholarly journals Vibration characteristics of triple-gear-rotor system in compressed air energy storage under variable torque load

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042098705
Author(s):  
Xinran Wang ◽  
Yangli Zhu ◽  
Wen Li ◽  
Dongxu Hu ◽  
Xuehui Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Element Model ◽  
Rotor System ◽  
Dynamic Responses ◽  
System Response ◽  
Rotating Speed ◽  
Torque Load ◽  
Set Up ◽  
Two Stages

This paper focuses on the effects of the off-design operation of CAES on the dynamic characteristics of the triple-gear-rotor system. A finite element model of the system is set up with unbalanced excitations, torque load excitations, and backlash which lead to variations of tooth contact status. An experiment is carried out to verify the accuracy of the mathematical model. The results show that when the system is subjected to large-scale torque load lifting at a high rotating speed, it has two stages of relatively strong periodicity when the torque load is light, and of chaotic when the torque load is heavy, with the transition between the two states being relatively quick and violent. The analysis of the three-dimensional acceleration spectrum and the meshing force shows that the variation in the meshing state and the fluctuation of the meshing force is the basic reasons for the variation in the system response with the torque load. In addition, the three rotors in the triple-gear-rotor system studied show a strong similarity in the meshing states and meshing force fluctuations, which result in the similarity in the dynamic responses of the three rotors.

Sign in / Sign up

Export Citation Format

Share Document