scholarly journals Change Detection for Building Footprints with Different Levels of Detail Using Combined Shape and Pattern Analysis

2018 ◽  
Vol 7 (10) ◽  
pp. 406 ◽  
Author(s):  
Xiaodong Zhou ◽  
Zhe Chen ◽  
Xiang Zhang ◽  
Tinghua Ai
Keyword(s):  
Change Detection ◽  
Urban Studies ◽  
Spatial Databases ◽  
Data Matching ◽  
Levels Of Detail ◽  
Heterogeneous Datasets ◽  
Rule Sets ◽  
The Many ◽  
Measurable Factors ◽  
Different Levels

Crowd-sourced geographic information is becoming increasingly available, providing diverse and timely sources for updating existing spatial databases to facilitate urban studies, geoinformatics, and real estate practices. However, the discrepancies between heterogeneous datasets present challenges for automated change detection. In this paper, we identify important measurable factors to account for issues like boundary mismatch, large offset, and discrepancies in the levels of detail between the more current and to-be-updated datasets. These factors are organized into rule sets that include data matching, merge of the many-to-many correspondence, controlled displacement, shape similarity, morphology of difference parts, and the building pattern constraint. We tested our approach against OpenStreetMap and a Dutch topographic dataset (TOP10NL). By removing or adding some components, the results show that our approach (accuracy = 0.90) significantly outperformed a basic geometric method (0.77), commonly used in previous studies, implying a more reliable change detection in realistic update scenarios. We further found that distinguishing between small and large buildings was a useful heuristic in creating the rules.

scholarly journals MCLEAN: Multilevel Clustering Exploration As Network

2018 ◽  
Vol 4 ◽  
pp. e145 ◽  
Author(s):  
Daniel Alcaide ◽  
Jan Aerts
Keyword(s):  
Data Analysis ◽  
Visual Analytics ◽  
User Study ◽  
R Package ◽  
Agglomerative Hierarchical Clustering ◽  
Levels Of Detail ◽  
Heterogeneous Datasets ◽  
Community Finding ◽  
Multilevel Representations ◽  
Different Levels

Finding useful patterns in datasets has attracted considerable interest in the field of visual analytics. One of the most common tasks is the identification and representation of clusters. However, this is non-trivial in heterogeneous datasets since the data needs to be analyzed from different perspectives. Indeed, highly variable patterns may mask underlying trends in the dataset. Dendrograms are graphical representations resulting from agglomerative hierarchical clustering and provide a framework for viewing the clustering at different levels of detail. However, dendrograms become cluttered when the dataset gets large, and the single cut of the dendrogram to demarcate different clusters can be insufficient in heterogeneous datasets. In this work, we propose a visual analytics methodology called MCLEAN that offers a general approach for guiding the user through the exploration and detection of clusters. Powered by a graph-based transformation of the relational data, it supports a scalable environment for representation of heterogeneous datasets by changing the spatialization. We thereby combine multilevel representations of the clustered dataset with community finding algorithms. Our approach entails displaying the results of the heuristics to users, providing a setting from which to start the exploration and data analysis. To evaluate our proposed approach, we conduct a qualitative user study, where participants are asked to explore a heterogeneous dataset, comparing the results obtained by MCLEAN with the dendrogram. These qualitative results reveal that MCLEAN is an effective way of aiding users in the detection of clusters in heterogeneous datasets. The proposed methodology is implemented in an R package available athttps://bitbucket.org/vda-lab/mclean.

scholarly journals MCLEAN: Multilevel Clustering Exploration As Network

2017 ◽  
Author(s):  
Daniel Alcaide ◽  
Jan Aerts
Keyword(s):  
Data Analysis ◽  
Visual Analytics ◽  
User Study ◽  
R Package ◽  
Agglomerative Hierarchical Clustering ◽  
Levels Of Detail ◽  
Heterogeneous Datasets ◽  
Community Finding ◽  
Multilevel Representations ◽  
Different Levels

Finding useful patterns in datasets has attracted considerable interest in the field of visual analytics. One of the most common tasks is the identification and representation of clusters. However, this is non-trivial in heterogeneous datasets since the data needs to be analyzed from different perspectives. Indeed, highly variable patterns may mask underlying trends in the dataset. Dendrograms are graphical representations resulting from agglomerative hierarchical clustering and provide a framework for viewing the clustering at different levels of detail. However, dendrograms become cluttered when the dataset gets large, and the single cut of the dendrogram to demarcate different clusters can be insufficient in heterogeneous datasets. In this work, we propose a visual analytics methodology called MCLEAN that offers a general approach for guiding the user through the exploration and detection of clusters. Powered by a graph-based transformation of the relational data, it supports a scalable environment for representation of heterogeneous datasets by changing the spatialization. We thereby combine multilevel representations of the clustered dataset with community finding algorithms. Our approach entails displaying the results of the heuristics to users, providing a setting from which to start the exploration and data analysis. To evaluate our proposed approach, we conduct a qualitative user study, where participants are asked to explore a heterogeneous dataset, comparing the results obtained by MCLEAN with the dendrogram. These qualitative results reveal that MCLEAN is an effective way of aiding users in the detection of clusters in heterogeneous datasets. The proposed methodology is implemented in an R package available at https://bitbucket.org/vda-lab/mclean

scholarly journals MCLEAN: Multilevel Clustering Exploration As Network

2017 ◽  
Author(s):  
Daniel Alcaide ◽  
Jan Aerts
Keyword(s):  
Data Analysis ◽  
Visual Analytics ◽  
User Study ◽  
R Package ◽  
Agglomerative Hierarchical Clustering ◽  
Levels Of Detail ◽  
Heterogeneous Datasets ◽  
Community Finding ◽  
Multilevel Representations ◽  
Different Levels

Finding useful patterns in datasets has attracted considerable interest in the field of visual analytics. One of the most common tasks is the identification and representation of clusters. However, this is non-trivial in heterogeneous datasets since the data needs to be analyzed from different perspectives. Indeed, highly variable patterns may mask underlying trends in the dataset. Dendrograms are graphical representations resulting from agglomerative hierarchical clustering and provide a framework for viewing the clustering at different levels of detail. However, dendrograms become cluttered when the dataset gets large, and the single cut of the dendrogram to demarcate different clusters can be insufficient in heterogeneous datasets. In this work, we propose a visual analytics methodology called MCLEAN that offers a general approach for guiding the user through the exploration and detection of clusters. Powered by a graph-based transformation of the relational data, it supports a scalable environment for representation of heterogeneous datasets by changing the spatialization. We thereby combine multilevel representations of the clustered dataset with community finding algorithms. Our approach entails displaying the results of the heuristics to users, providing a setting from which to start the exploration and data analysis. To evaluate our proposed approach, we conduct a qualitative user study, where participants are asked to explore a heterogeneous dataset, comparing the results obtained by MCLEAN with the dendrogram. These qualitative results reveal that MCLEAN is an effective way of aiding users in the detection of clusters in heterogeneous datasets. The proposed methodology is implemented in an R package available at https://bitbucket.org/vda-lab/mclean

Development of a Simulation-Based Process Chain – Strategy for Different Levels of Detail for the Preprocessing Definitions

2011 ◽  
Vol 21 (3-4) ◽  
pp. 135-140 ◽  
Author(s):  
Toni A. Krol ◽  
Sebastian Westhäuser ◽  
M. F. Zäh ◽  
Johannes Schilp ◽  
G. Groth
Keyword(s):  
Process Chain ◽  
Levels Of Detail ◽  
Simulation Based ◽  
Different Levels

scholarly journals The 4-Level Approach: Prevention of Suicidal Behaviour Through Community-Based Intervention

2021 ◽  
Vol 12 ◽  
Author(s):  
Ulrich Hegerl ◽  
Ines Heinz ◽  
Ainslie O'Connor ◽  
Hannah Reich
Keyword(s):  
Public Health ◽  
Primary Care ◽  
High Risk ◽  
Suicidal Behaviour ◽  
Lessons Learned ◽  
Community Based Interventions ◽  
Community Based ◽  
Four Levels ◽  
The Many ◽  
Different Levels

Due to the many different factors contributing to diagnostic and therapeutic deficits concerning depression and the risk of suicidal behaviour, community-based interventions combining different measures are considered the most efficient way to address these important areas of public health. The network of the European Alliance Against Depression has implemented in more than 120 regions within and outside of Europe community-based 4-level-interventions that combine activities at four levels: (i) primary care, (ii) general public, (iii) community facilitators and gatekeepers (e.g., police, journalists, caregivers, pharmacists, and teachers), and (iv) patients, individuals at high risk and their relatives. This review will discuss lessons learned from these broad implementation activities. These include targeting depression and suicidal behaviour within one approach; being simultaneously active on the four different levels; promoting bottom-up initiatives; and avoiding any cooperation with the pharmaceutical industry for reasons of credibility.

Projection between Exhibition and Information

2020 ◽  
pp. 211-236
Author(s):  
Adeena Mey
Keyword(s):  
Research Group ◽  
Spatial Relations ◽  
Media History ◽  
Land Art ◽  
Earth History ◽  
Moving Images ◽  
Entire Country ◽  
The Many ◽  
Different Levels ◽  
The Way

Among the many reconfigurations and experiments with the ‘medium of the exhibition’ of the 1960–1970s, Sonsbeek 71 stands as one the most audacious examples. Organized by curator Wim Beeren as an attempt to find a new curatorial language and innovative exhibition form, Sonsbeek 71 took ‘the entire country as its field of operation’, the ‘exhibition’ consisting of several works of land art, ‘information centres’, as well as pavilions dedicated to film, video, and art mediation. The ‘spatial relations’ exposed by the scale of this apparatus became the very object of Beeren’s curatorial inquiry. Focusing on projected moving images at Sonsbeek 71, this chapter discusses it on three different levels. First, it identifies the way both the film and exhibition apparatus were reconfigured and how Sonsbeek 71 functioned as an epistemology of the exhibition as medium. Second, it articulates a critique of the exhibition as a form intersecting technical, discursive, informational, and sensible elements, and shows how, in its radical expansion of the exhibition medium, Sonsbeek 71 ‘conflates media history with earth history’ (Parikka). Third, what is meant by the notion of the exhibition as ‘medium’ is discussed in light of the inflatable pavilions designed by the Eventstructure Research Group where structural films and artists’ films were projected. This eventually opens up to a critique of the informational, cybernetic epistemology of Sonsbeek 71.

Types of cooperation and networks

2019 ◽  
pp. 101-122
Author(s):  
John Child ◽  
David Faulkner ◽  
Stephen Tallman ◽  
Linda Hsieh
Keyword(s):  
Joint Ventures ◽  
Strategic Alliance ◽  
International Expansion ◽  
Expansion Joint ◽  
Alliances And Joint Ventures ◽  
Different Types ◽  
Supplier Contracts ◽  
The Many ◽  
Different Levels

Chapter 5 reviews the traditional forms of strategic alliance and network. It shows that there are many different types, ranging from supplier contracts to equity joint ventures, and all have different levels of interaction and independence. Networks are another well-established form of cooperation; these can embrace several, sometimes many, firms and other partners. This chapter discusses dominated, equal partner, and coordinated networks. This chapter also describes a variety of taxonomies proposed for classifying alliances. It notes that Yoshino and Rangan (1995) and Dussauge and Garrette (1999) have perhaps the most attractive typologies of alliance forms among the many on offer. Yoshino and Rangan categorize alliances into non-traditional contracts, equity alliances, and joint ventures. Dussauge and Garrette identify international expansion joint ventures, vertical partnerships, diversification alliances, complementary alliances, shared supply alliances, and quasi-concentration alliances. The chapter concludes with some suggestions as to which forms may be most appropriate for which situations.

Thrombocytosis

2010 ◽  
pp. 4280-4287
Author(s):  
Stefan O. Ciurea ◽  
Ronald Hoffman
Keyword(s):  
Stem Cell ◽  
Platelet Count ◽  
Iron Deficiency ◽  
Blood Loss ◽  
Haematopoietic Stem Cell ◽  
Polycythaemia Vera ◽  
Essential Thrombocythaemia ◽  
Platelet Production ◽  
The Many ◽  
Different Levels

Thrombocytosis describes a platelet count elevated above 450 × 109/litre, which can be (1) primary—including essential thrombocythaemia, chronic myeloid leukaemia, polycythaemia vera and myelodysplastic syndromes; or (2) secondary—including iron deficiency, infection, blood loss, malignancy. Platelets are released from megakaryocytes, whose development is principally regulated by thrombopoietin. This is chiefly produced in the liver and binds to its receptor (c-Mpl) to cause activation via the JAK-STAT signalling pathway at different levels of the platelet production pathway, ranging from the proliferation and survival of haematopoietic stem cell/progenitor cells to megakaryocyte maturation. Thrombopoietin production is increased by a wide variety of stimuli, which explains the many causes of secondary thrombocytosis....

Architecture for Symbolic Object Warehouse

2009 ◽  
pp. 648-657
Author(s):  
Sandra Elizabeth González Císaro ◽  
Héctor Oscar Nigro
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Complex Data ◽  
Data Complexity ◽  
Intrinsic Structure ◽  
Levels Of Detail ◽  
Decision Making Processes ◽  
Design Systems ◽  
Central Database ◽  
Different Levels

Much information stored in current databases is not always present at necessary different levels of detail or granularity for Decision-Making Processes (DMP). Some organizations have implemented the use of central database - Data Warehouse (DW) - where information performs analysis tasks. This fact depends on the Information Systems (IS) maturity, the type of informational requirements or necessities the organizational structure and business own characteristic. A further important point is the intrinsic structure of complex data; nowadays it is very common to work with complex data, due to syntactic or semantic aspects and the processing type (Darmont et al., 2006). Therefore, we must design systems, which can to maintain data complexity to improve the DMP.

Kinetics Study of the Acidic Catalyzed Polymerization of Tetraethoxysilane by 29Si NMR.

1988 ◽  
Vol 121 ◽  
Author(s):  
Jean-Claude Pouxviel ◽  
J. P. Boilot
Keyword(s):  
Significant Contribution ◽  
Hydrolysis Rate ◽  
Hydroxyl Groups ◽  
29Si Nmr ◽  
Condensation Reactions ◽  
Levels Of Detail ◽  
Degree Of Condensation ◽  
By Products ◽  
Different Levels

ABSTRACTTEOS has been hydrolysed under acidic condition with stoichiome-tric or excess amount of water. Evolution of the silicon species is followed by 29Si NMR. The data are analyzed at different levels of detail; first, analysis of the by products of polymerization reactions, second determination of the extents and overall rate constants of hydrolysis and condensation reactions and finally kinetics simulations of the evolution taking into account all the present silicon species. We have shown that the hydrolysis rate increases with the number of hydroxyl groups, and the reesterification reactions have a significant contribution. We also found that condensation reactions preferentially occur with loss of water between the more hydrolyzed monomers; their rates rapidly decrease with the degree of condensation. We compare the two compositions as a function of their water content and pH.

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