scholarly journals Spatio-temporal encoding by quadratic gradients in magnetic resonance imaging

2019 ◽  
Author(s):  
Sina Marhabaie ◽  
Geoffrey Bodenhausen ◽  
Philippe Pelupessy
Keyword(s):  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Magnetic Field Gradient ◽  
Quadratic Function ◽  
Transverse Magnetization ◽  
Chirp Pulse ◽  
Simultaneous Application ◽  
Quadratic Phase ◽  
Temporal Encoding ◽  
Spatio Temporal

Abstract. SPatio-temporal ENcoding (SPEN) MRI is a non-Fourier imaging technique that encodes the spatial information in such a way that there is a one-to-one correspondence between the signal intensity as a function of time and the spin density at the corresponding position. In current spatio-temporal encoding methods imparting a quadratic phase – that is the phase of the transverse magnetization depends as a quadratic function of the spatial coordinates – onto the transverse magnetization is the first crucial step. Usually, this is achieved by simultaneous application of a frequency-swept (chirp) pulse and a linear magnetic field gradient. In this work, we show that it can be advantageous to use quadratic encoding gradients for this purpose. By avoiding chirp pulses one can achieve much smaller specific absorption rates (SARs), and shorter echo times (TEs), while the spatial resolution, the field of view (FOV), and the signal-to-noise ratio (SNR) are the same as in SPEN if one uses similar parameters. In addition, the proposed sequence can readily be used for multi-slice applications.

scholarly journals The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective

2021 ◽  
Vol 10 (3) ◽  
pp. 166
Author(s):  
Hartmut Müller ◽  
Marije Louwsma
Keyword(s):  
European Union ◽  
Spatial Distribution ◽  
Spatial Information ◽  
National Level ◽  
Temporal Information ◽  
The European Union ◽  
Member States ◽  
Heavy Burden ◽  
Spatio Temporal

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of spatio-temporal information in governing the pandemic in the European Union and its member states. The European Nomenclature of Territorial Units for Statistics (NUTS) system and selected national dashboards from member states were assessed to analyze which spatio-temporal information was used, how the information was visualized and whether this changed over the course of the pandemic. Initially, member states focused on their own jurisdiction by creating national dashboards to monitor the pandemic. Information between member states was not aligned. Producing reliable data and timeliness reporting was problematic, just like selecting indictors to monitor the spatial distribution and intensity of the outbreak. Over the course of the pandemic, with more knowledge about the virus and its characteristics, interventions of member states to govern the outbreak were better aligned at the European level. However, further integration and alignment of public health data, statistical data and spatio-temporal data could provide even better information for governments and actors involved in managing the outbreak, both at national and supra-national level. The Infrastructure for Spatial Information in Europe (INSPIRE) initiative and the NUTS system provide a framework to guide future integration and extension of existing systems.

scholarly journals Spatio-Temporal Alignment and Trajectory Matching for Netted Radar Without Prior Spatial Information and Time Delay

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 126965-126976
Author(s):  
Xiaoyu Cong ◽  
Yubing Han ◽  
Weixing Sheng ◽  
Shanhong Guo ◽  
Renli Zhang
Keyword(s):  
Time Delay ◽  
Spatial Information ◽  
Temporal Alignment ◽  
Trajectory Matching ◽  
Spatio Temporal

VIDEO-SHOT TRANSITION DETECTION: A SPATIO-TEMPORAL SALIENCY APPROACH

2010 ◽  
Vol 24 (08) ◽  
pp. 1295-1309 ◽  
Author(s):  
XIAN WU ◽  
JIANHUANG LAI ◽  
PONG C. YUEN
Keyword(s):  
Error Probability ◽  
Spatial Information ◽  
Saliency Map ◽  
Detection Error ◽  
Novel Approach ◽  
Video Shot ◽  
Recent Method ◽  
Temporal And Spatial ◽  
Spatio Temporal ◽  
Shot Transitions

This paper proposes a novel approach for video-shot transition detection using spatio-temporal saliency. Both temporal and spatial information are combined to generate a saliency map, and features are available based on the change of saliency. Considering the context of shot changes, a statistical detector is constructed to determine all types of shot transitions by the minimization of the detection-error probability simultaneously under the same framework. The evaluation performed on videos of various content types demonstrates that the proposed approach outperforms a more recent method and two publicly available systems, namely VideoAnnex and VCM.

scholarly journals IDENTIFYING OVERLAPPED OBJECTS FOR VIDEO INDEXING AND MODELING IN MULTIMEDIA DATABASE SYSTEMS

2001 ◽  
Vol 10 (04) ◽  
pp. 715-734 ◽  
Author(s):  
SHU-CHING CHEN ◽  
MEI-LING SHYU ◽  
CHENGCUI ZHANG ◽  
R. L. KASHYAP
Keyword(s):  
Spatial Information ◽  
Video Segmentation ◽  
Database Systems ◽  
Video Indexing ◽  
Video Data ◽  
Multimedia Database ◽  
Current Frame ◽  
Data Indexing ◽  
Spatio Temporal ◽  
Input Strings

The identification of the overlapped objects is a great challenge in object tracking and video data indexing. For this purpose, a backtrack-chain-updation split algorithm is proposed to assist an unsupervised video segmentation method called the "simultaneous partition and class parameter estimation" (SPCPE) algorithm to identify the overlapped objects in the video sequence. The backtrack-chain-updation split algorithm can identify the split segment (object) and use the information in the current frame to update the previous frames in a backtrack-chain manner. The split algorithm provides more accurate temporal and spatial information of the semantic objects so that the semantic objects can be indexed and modeled by multimedia input strings and the multimedia augmented transition network (MATN) model. The MATN model is based on the ATN model that has been used in artificial intelligence (AI) areas for natural language understanding systems, and its inputs are modeled by the multimedia input strings. In this paper, we will show that the SPCPE algorithm together with the backtrack-chain-updation split algorithm can significantly enhance the efficiency of spatio-temporal video indexing by improving the accuracy of multimedia database queries related to semantic objects.

scholarly journals SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA

2011 ◽  
Vol 19 (3) ◽  
pp. 189
Author(s):  
Karsten Rodenacker ◽  
Klaus Hahn ◽  
Gerhard Winkler ◽  
Dorothea P Auer
Keyword(s):  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Digital Data ◽  
Linear Filters ◽  
Brain Functions ◽  
Non Linear ◽  
Long Time ◽  
Spatio Temporal ◽  
Sensory Activation ◽  
Temporal Data Analysis

Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging) are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D) is gathered during relatively long time ranges (3-5 min). From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters). Filters applied are compared by classifications of activations.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Athanasios Tom Kralidis ◽  
Ntabathia Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Spatial Information ◽  
National Endowment ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use “any means necessary” to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations, feedback mechanisms based on log mining, usage statistic gathering, and many others. In this paper we will be focusing on improving geospatial search with a search engine platform that uses Lucene, a Java-based search library, at its core. In work funded by the National Endowment for the Humanities, the Centre for Geographic Analysis (CGA) at Harvard University is in the process of re-engineering the search component of its public domain SDI (WorldMap http://worldmap.harvard.edu ) which is based on the GeoNode platform. In the process the CGA has developed Harvard Hypermap (HHypermap), a map services registry and search platform independent from WorldMap. The goal of HHypermap is to provide a framework for building and maintaining a comprehensive registry of web map services, and because such a registry is expected to be large, the system supports the development of clients with modern search capabilities such as spatial and temporal faceting and instant previews via an open API. Behind the scenes HHypermap scalably harvests OGC and Esri service metadata from distributed servers, organizes that information, and pushes it to a search engine. The system monitors services for reliability and uses that to improve search. End users will be able to search the SDI metadata using standard interfaces provided by the internal CSW catalogue, and will benefit from the enhanced search possibilities provided by an advanced search engine. HHypermap is built on an open source software source stack.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Text Search ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Database Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software component of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogs and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalog, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

scholarly journals DEVELOPING A 3-D GIS MODEL FOR URBAN PLANNING. CASE STUDY: AMPANG JAYA, MALAYSIA

2018 ◽  
Vol 16 (7) ◽  
Author(s):  
Mimi Zaleha Abdul Ghani ◽  
Yazid Sarkom ◽  
Zalina Samadi
Keyword(s):  
Decision Making ◽  
Urban Planning ◽  
Spatial Information ◽  
Gis Model ◽  
Written Information ◽  
Urban Planning And Design ◽  
Spatio Temporal ◽  
The Rich ◽  
Interactive Visualisation

This paper aims to explore the rich potential of interactive visualisation environment integrating GIS for modelling urban growth and spatio-temporal transformation of Malaysian cities. As a case study example, authors consider a 3-D GIS model of Ampang Jaya, Selangor to investigate the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualisation in constructing a digital model ranging from low to high geometric content including 2-D digital maps, digital orthographic and full volumetricparametric modelling. The key aspect of this virtual model is how it would assist in understanding the urban planning and design of Ampang Jaya by translating complex spatial information that are currently used by the authorities for planning activities such as maps, plans and written information into responsive, easily understandable spatial information. It could serve as a new platform to disseminate information about Ampang Jaya, bridge gaps among professionals involved in planning processes, improve communications among decision makers, stakeholders and the public as well as support decision making about thespatial growth of Ampang Jaya. Demonstrations of Ampang Jaya will also provide a clearer picture of the importance of ownership and control of 3-D models by local councils in empowering them in decision making, for example, in improving transparency, and avoiding misuse by project developers (Shiffer 1993; Sunesson et al., 2008). Such environment will improve the subsequent digital models and research in the area of urban design and planning in Malaysia where visual communication is pivotal.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

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