7Th Belgium Geography Day

Total Page:16

File Type:pdf, Size:1020Kb

7Th Belgium Geography Day 7th Belgium Geography Day 17th November 2017 ABSTRACTS 7th Belgium Geography Day Table of contents Program of the day 9 Oral presentations in Geomatics - Theme 1. Remote-sensing Keynote presentation: Big Data and Geomatics : towards a new management of J.P. Kasprzyk, P. Hallot 11 spatial information Introduction: The last decades revolutions in Remote Sensing : example F. Kervyn 12 of implications for Earth Science CraterNet: a fully convolutional neural network for lunar Q. Glaude, Y. Cornet 13 crater detection based on remotely sensed data Tracking forest degradation with high-resolution 3D forest B. Gobbi, V. Vanacker, A. Van 14 maps Rompaey, I. Gasparri Using Sentinel-2 and imaging spectroscopy for sub-pixel F. Priem, A. Okujeni, S. van der 15 mapping of urban areas Linden, F. Canters Combining Satellite, Airborne and Ground-Based Remote Sensing Techniques to study the Lava Lake Activity of B. Smets, N. d’Oreye, F. Kervyn 16 Nyiragongo Volcano (North Kivu, D.R. Congo) A batch-processing assessment of AquaCrop plug-in for J. Wellens, A. M. Sallah, B. 17 maize and winter wheat Tychon, et al. Oral presentations in Geomatics - Theme 2. Data acquisition Introduction: R. Warnant, C. Deprez, Q. Precise positioning with smartphones running Android 7 or 18 Warnant later Precise positioning in multi-GNSS mode C. Deprez, R. Warnant 19 A multi-sensor approach to characterize landslide A. Dille, Elise Monsieurs, A. Nobile, 20 dynamics in a tropical urban environment et al. Using UAV and SfM to understand the geomorphological H. Hendrickx, R. Delaloye, J. 21 dynamics on periglacial talus slopes Nyssen, A. Frankl From 3D physical data to 3D intelligent point clouds F. Poux, R. Billen 22 N. Vanhaeren, L. De Cock, B. De AVs and 3D modelling in South America 23 Wit Oral presentations in Geomatics - Theme 3. Fundamental and applied GIS Introduction: N. Van de Weghe 24 GIS: from systems over science towards technology Revisiting the internal structure of Brussels with mobile phone data and socio-economics variable: do we A. Adam, I. Thomas 25 converge? Geography, Statistics and LCA: combine and interface methods to map territorial inequalities of environmental S. Bourrelly 26 impacts arising from land use planning designed by public policy Viewpoint management for an optimal 3D visualisation R. Neuville 27 On measuring “green”: a comparative analysis of four S. Trabelsi, I. Thomas 28 databases in Namur (Belgium) GI Learner: Developing a learning line on GIScience in L. Zwartjes 29 education Posters in Geomatics Estimation of Forest Biomass Using Remotely Sensed Data in T. Altanchimeg, T. Renchin, P. De 31 Northern Part of Mongolia Maeyer, B. Tseveen Soil Organic Carbon prediction in croplands by airborne F. Castaldi, B. van Wesemael, S. 32 APEX images using LUCAS topsoil database Chabrillat Exploring the evolving structure of the Southeast Asian air L. Dai, B. Derudder, X. Liu 33 transport network during 1979-2012 E. Natsagdorj, T. Renchin, P. De Soil Moisture Analysis Using Multispectral Data in Mongolia 34 Maeyer, B. Tseveen Using of European’s satellite images, Sentinel-2 and hydrometric data for monitoring the surface water S. Pale, F. Traore, J. Wellens, B. 35 abstraction, for agricultural purpose, in the sub-basin Tychon Upper-Comoé, Burkina Faso Cartesius.be – The world in old maps, aerial photographs R. W. Kruk 36 and drawings online in your class room Oral presentations in Physical Geography - Theme 1. Geo-hazard Keynote presentation: J. Poesen 38 Why Geomorphology matters? Introduction: Geo-hazards: Research Achievements, Challenges and M. Kervyn 39 Perspectives To which extend inundations are influenced by urban M. Bruwier, P. Archambeau, S. 40 patterns? Erpicum, M. Pirotton, B. Dewals « Cap-Haïtien » or « how to ‘construct’ a flood risk in a G. J. Gracius, P. Ozer 41 decade » Land transactions to change risk exposure? Landslides, land K. Mertens, L. Vranken 42 markets and social norms T. Mugaruka Bibentyo, S. Anatomy of Nyakavogo landslide (Bukavu, DR Congo): Kulimushi Matabaro, W. Muhindo 43 interplay between natural and anthropogenic factors Sahani, O. Dewitte Geohazards and flood risk assessment in Bujumbura / L. Nibigira, H.-B. Havenith, P. 44 Burundi: Contribution of Numerical Modeling Archambeau, B. Dewals Oral presentations in Physical Geography - Theme 2. Long-term geomorphology Introduction: V. Vanacker, N. Vandermaelen, Constraining landscape evolution over 10 yr, 10 ky and 1 B. Campforts, J. Schoonejans, K. 45 my time scales Beerten Quantifying long-term human impact in contrasting N. Broothaerts, J.A. López-Sáez, 46 environments: a palynological and statistical approach G. Verstraeten From landslide to alluvial fan: a process based model to B. Campforts, W. Schwanghart, evaluate the influence of sediment production and 47 V. Vanacker, G. Govers transport on landscape evolution Long-term erosion rates in an earthflow-affected watershed F. Clapuyt, V. Vanacker, F. 48 in the Central Swiss Alps Schlunegger, K. Van Oost Using lacustrine sediments to record past natural hazards: L. Lamair, A. Hubert-Ferrari, S. 49 The case of Fuji Five Lakes (Japan) Yamamoto, et al. Impacts of the conversion of forest to arable land and long J. Robinet, J.P.G. Minella, C.A. P. term agriculture practices on the water pathways in 50 de Barros, et al. Southern Brazil Oral presentations in Physical Geography - Theme 3. Contemporary geomorphic processes, land degradation, and soil and water conservation Introduction: Challenges and opportunities regarding land degradation C. L. Bielders 51 and soil conservation Environmental flow assessment in Andean rivers of Ecuador, I. Alomía Herrera, P. Carrera case study: Chanlud and El Labrado dams in the 52 Burneo Machangara River Impacts of land use and cover changes on the hydrology A. Birhanu, I. Masihb, X. Caib, J. 53 of Gumara catchment, Ethiopia Nyssenc, P. van der Zaag Weir impacts on sediment transport and geomorphic A. Peeters, F. Petit, G. Houbrechts 54 response to their removal in the Bocq River (Belgium) Spatial environmental determinants of the risk of tick-borne R. Rousseau 55 diseases in Walloon pastures Climate and environment in biological theory S. Rubin 56 Posters in Physical Geography Vulnérabilité aux inondations dans le contexte des A. Amanejeiu, R.A. Feumba, R. changements climatiques à New-Bell Ngangue, un quartier 58 Ngoufo, P. Ozer planifie de la ville de Douala, Cameroun J. Broeckx, M. Vanmaercke, R. A data-based landslide susceptibility map of Africa 59 Duchateau , J. Poesen Les stratégies d’adaptation face au risque d’inondation S. Bronfort, H. Yénoukoumè 60 dans les zones d’habitat spontané Hangnon, P. Ozer Risk management in Ivory Coast: Case Study of Population B.R. Comoe, P. Ozer 61 Evictions in Port-Bouët, Abidjan Assessing the impacts of farming practices and soil and water conservation measures on soil erosion in South-Kivu, A.B. Heri-Kazi, C.L. Builders 62 Eastern D.R. Congo Vulnérabilité et adaptation des communautés lacustres M.A. Lokossou, F. De Longueville, aux inondations à Sô-Ava dans la basse vallée de l’Ouémé 63 P. Ozer au Bénin Social multi-criteria evaluation to identify appropriate J. Maes, J. Poesen, L. Vranken, et landslide risk reduction measures: Application for the 64 al. Rwenzori Mountains, Uganda F. Makanzu Imwangana, J. Gully erosion in Kinshasa: hydromorphogenic dynamics and Moeyersons, P. Ozer, M. Ntombi, 65 development of prevention tools O. Dewitte Karstic phenomena of the BOUKADIR-Chlef. Geological, M.L. Moulana, M. Guendouz, A. 66 hydrogeological and mineralogical characterization Hubert-Ferrari Understanding water level fluctuations in (semi)closed H. Meaza, J. Nyssen, J. Poesen, et marginal grabens under a fast growing irrigation 67 al. development of north Ethiopia Contextual analysis of Algerian floods between 1921 and M. Nouri, J.M. Halleux, P. Ozer 68 2016 Recent evolution of the coastline in the Gulf of Guinea. P. Ozer, Y.C. Hountondji, F. De 69 Example of Togo and Benin (2000-2015) Longueville Removal of impurities released from phosphogypsum waste O. Safae, G. Elkhadir, N. Fagel, M. 70 in aquatic environment using bentonite El Ouahabi Recent rock avalanches on Mt Baker, Rwenzori Mountains (Uganda, D.R. Congo): an example of landslide D. Samyn, N. Hisette, C. 71 reconstruction in a remote, rugged, data-poor mountain Kabaseke, L. Jacobs, F. Kervyn environment Modelling blanket peatland hydrology and Holocene W. Swinnen, N. Broothaerts, G. 72 peatland development in north-eastern Scotland Verstraeten Analyse spatio-temporelle de la vulnérabilité de la A.M. Syavulisembo, C. Michellier, Population face à l’aléa Volcanique : le cas de Goma, 73 E. Wolff, F. Kervyn République Démocratique du Congo Exposition et vulnérabilité face aux risques d’inondation au Y.D. Tomety, B. Dewals, P. Ozer 74 Burkina Faso : Cas de la ville de Dori Constraining exposure age and erosion rates of the N. Vandermaelen, V. Vanacker, 75 Kempen Plateau over the last 1 Ma K. Beerten Effectiveness of plant roots in controlling rill and gully W. Vannoppen, J. Poesen, S. De erosion: A case study on vegetation communities on river 76 Baets, et al. dikes Spatial distribution of rock fragments in purple soil in Three X. Wang, T. Wang, C. Cai, B. He 77 Gorges Reservoir Area The African Anthropocene: land-use history in the central Rift Valley of Kenya based on analyses of clay minerals, T. Wuytack , G. De Cort, G. Van 78 particle size and charcoal in a continuous lake-sediment Der Plas, et al. record Contribution des systèmes d’information géographique M.O. Zogning Moffo, P. Ozer, B. pour la Cartographie des zones à risques d’inondation à 79 Dewals Yaounde Oral presentations in Urban, Economic and Rural Geography - Theme 1. Cities Keynote presentation: Contested entangled geographies: Challenges and M. van Meeteren 81 relevance of Belgian human-geographical research Introduction: J.-M. Halleux 82 Urban geography at the heart of the urban transition Who’s the ‘green’ for? The social inclusion/exclusion of A.
Recommended publications
  • Scikit-Network Documentation Release 0.24.0 Bertrand Charpentier
    scikit-network Documentation Release 0.24.0 Bertrand Charpentier Jul 27, 2021 GETTING STARTED 1 Resources 3 2 Quick Start 5 3 Citing 7 Index 205 i ii scikit-network Documentation, Release 0.24.0 Python package for the analysis of large graphs: • Memory-efficient representation as sparse matrices in the CSR formatof scipy • Fast algorithms • Simple API inspired by scikit-learn GETTING STARTED 1 scikit-network Documentation, Release 0.24.0 2 GETTING STARTED CHAPTER ONE RESOURCES • Free software: BSD license • GitHub: https://github.com/sknetwork-team/scikit-network • Documentation: https://scikit-network.readthedocs.io 3 scikit-network Documentation, Release 0.24.0 4 Chapter 1. Resources CHAPTER TWO QUICK START Install scikit-network: $ pip install scikit-network Import scikit-network in a Python project: import sknetwork as skn See examples in the tutorials; the notebooks are available here. 5 scikit-network Documentation, Release 0.24.0 6 Chapter 2. Quick Start CHAPTER THREE CITING If you want to cite scikit-network, please refer to the publication in the Journal of Machine Learning Research: @article{JMLR:v21:20-412, author= {Thomas Bonald and Nathan de Lara and Quentin Lutz and Bertrand Charpentier}, title= {Scikit-network: Graph Analysis in Python}, journal= {Journal of Machine Learning Research}, year={2020}, volume={21}, number={185}, pages={1-6}, url= {http://jmlr.org/papers/v21/20-412.html} } scikit-network is an open-source python package for the analysis of large graphs. 3.1 Installation To install scikit-network, run this command in your terminal: $ pip install scikit-network If you don’t have pip installed, this Python installation guide can guide you through the process.
    [Show full text]
  • A Survey of Results on Mobile Phone Datasets Analysis
    Blondel et al. RESEARCH A survey of results on mobile phone datasets analysis Vincent D Blondel1*, Adeline Decuyper1 and Gautier Krings1,2 *Correspondence: [email protected] Abstract 1Department of Applied Mathematics, Universit´e In this paper, we review some advances made recently in the study of mobile catholique de Louvain, Avenue phone datasets. This area of research has emerged a decade ago, with the Georges Lemaitre, 4, 1348 increasing availability of large-scale anonymized datasets, and has grown into a Louvain-La-Neuve, Belgium Full list of author information is stand-alone topic. We will survey the contributions made so far on the social available at the end of the article networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues. Keywords: mobile phone datasets; big data analysis 1 Introduction As the Internet has been the technological breakthrough of the ’90s, mobile phones have changed our communication habits in the first decade of the twenty-first cen- tury. In a few years, the world coverage of mobile phone subscriptions has raised from 12% of the world population in 2000 up to 96% in 2014 – 6.8 billion subscribers – corresponding to a penetration of 128% in the developed world and 90% in de- veloping countries [1]. Mobile communication has initiated the decline of landline use – decreasing both in developing and developed world since 2005 – and allows people to be connected even in the most remote places of the world. In short, mobile phones are ubiquitous.
    [Show full text]
  • Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large
    Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks Raghvendra Mall, Rocco Langone and Johan A.K. Suykens Department of Electrical Engineering, KU Leuven, ESAT-STADIUS, Kasteelpark Arenberg,10 B-3001 Leuven, Belgium {raghvendra.mall,rocco.langone,johan.suykens}@esat.kuleuven.be Abstract Kernel spectral clustering corresponds to a weighted kernel principal compo- nent analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a repre- sentative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is de- termined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community de- arXiv:1411.7640v2 [cs.SI] 2 Dec 2014 tection techniques like the Louvain, OSLOM and Infomap methods. We show a major advantage our proposed approach i.e. the ability to locate good quality clusters at both the coarser and finer levels of hierarchy using internal cluster quality metrics on 7 real-life networks.
    [Show full text]
  • Xerox University Microfilms
    INFORMATION TO USERS This material was produced from a microfilm copy of the original document. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the original submitted. The following explanation of techniques is provided to help you understand markings or patterns which may appear on this reproduction. I.The sign or "target" for pages apparently lacking from the document photographed is "Missing Page(s)". If it was possible to obtain the missing page(s) or section, they are spliced into the film along with adjacent pages. This may have necessitated cutting thru an image and duplicating adjacent pages to insure you complete continuity. 2. When an image on the film is obliterated with a large round black mark, it is an indication that the photographer suspected that the copy may have moved during exposure and thus caijse a blurred image. You will find a good image of die page in the adjacent frame. 3. When a map, drawing or chart, etif., was part of the material being photographed the photographer followed a definite method in "sectioning" the material. It is customary to begin photoing at the upper left hand corner of a large sheet ang to continue photoing from left to right in equal sections with a small overlap. If necessary, sectioning is continued again — beginning below tf e first row and continuing on until complete. 4. The majority of users indicate that thetextual content is of greatest value, however, a somewhat higher quality reproduction could be made from "photographs" if essential to the understanding of the dissertation.
    [Show full text]
  • Fast Community Detection Using Local Neighbourhood Search
    Fast community detection using local neighbourhood search Arnaud Browet,∗ P.-A. Absil, and Paul Van Dooren Universit´ecatholique de Louvain Department of Mathematical Engineering, Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM) Av. Georges Lema^ıtre 4-6, B-1348 Louvain-la-Neuve, Belgium. (Dated: August 30, 2013) Communities play a crucial role to describe and analyse modern networks. However, the size of those networks has grown tremendously with the increase of computational power and data storage. While various methods have been developed to extract community structures, their computational cost or the difficulty to parallelize existing algorithms make partitioning real networks into commu- nities a challenging problem. In this paper, we propose to alter an efficient algorithm, the Louvain method, such that communities are defined as the connected components of a tree-like assignment graph. Within this framework, we precisely describe the different steps of our algorithm and demon- strate its highly parallelizable nature. We then show that despite its simplicity, our algorithm has a partitioning quality similar to the original method on benchmark graphs and even outperforms other algorithms. We also show that, even on a single processor, our method is much faster and allows the analysis of very large networks. PACS numbers: 89.75.Fb, 05.10.-a, 89.65.-s INTRODUCTION ity is encoded in the edge weight, this task is known in graph theory as community detection and has been introduced by Newman [9]. Community detection has Over the years, the evolution of information and com- already proven to be of great interest in many different munication technology in science and industry has had research areas such as epidemiology [10], influence and a significant impact on how collected data are being spread of information over social networks [11, 12], anal- used to understand and analyse complex phenomena [1].
    [Show full text]
  • A Survey of Results on Mobile Phone Datasets Analysis
    Blondel et al. EPJ Data Science (2015)4:10 DOI 10.1140/epjds/s13688-015-0046-0 R E V I E W Open Access A survey of results on mobile phone datasets analysis Vincent D Blondel1*, Adeline Decuyper1 and Gautier Krings1,2 *Correspondence: [email protected] Abstract 1Department of Applied Mathematics, Université catholique In this paper, we review some advances made recently in the study of mobile phone de Louvain, Avenue Georges datasets. This area of research has emerged a decade ago, with the increasing Lemaitre, 4, Louvain-La-Neuve, availability of large-scale anonymized datasets, and has grown into a stand-alone 1348, Belgium Full list of author information is topic. We survey the contributions made so far on the social networks that can be available at the end of the article constructed with such data, the study of personal mobility, geographical partitioning, urban planning,andhelp towards development as well as security and privacy issues. Keywords: mobile phone datasets; big data analysis; data mining; social networks; temporal networks; geographical networks 1 Introduction As the Internet has been the technological breakthrough of the ’s, mobile phones have changed our communication habits in the first decade of the twenty-first century. In a few years, the world coverage of mobile phone subscriptions has raised from % of the world population in up to % in - . billion subscribers - corresponding to a penetration of % in the developed world and % in developing countries []. Mobile communication has initiated the decline of landline use - decreasing both in developing and developed world since - and allows people to be connected even in the most remote places of the world.
    [Show full text]
  • Generalized Louvain Method for Community Detection in Large Networks
    Generalized Louvain method for community detection in large networks Pasquale De Meo∗, Emilio Ferrarax, Giacomo Fiumara∗, Alessandro Provetti∗,∗∗ ∗Dept. of Physics, Informatics Section. xDept. of Mathematics. University of Messina, Italy. ∗∗Oxford-Man Institute, University of Oxford, UK. fpdemeo, eferrara, gfiumara, [email protected] Abstract—In this paper we present a novel strategy to a novel measure of edge centrality, in order to rank all discover the community structure of (possibly, large) networks. the edges of the network with respect to their proclivity This approach is based on the well-know concept of network to propagate information through the network itself; iii) modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ-paths. its computational cost is low, making it feasible even for This technique allows to efficiently compute a edge ranking large network analysis; iv) it is able to produce reliable in large networks in near linear time. Once the centrality results, even if compared with those calculated by using ranking is calculated, the algorithm computes the pairwise more complex techniques, when this is possible; in fact, proximity between nodes of the network. Finally, it discovers because of the computational constraints, the adoption of the community structure adopting a strategy inspired by the well-known state-of-the-art Louvain method (henceforth, LM), some existing techniques is not viable when considering efficiently maximizing the network modularity. The experi- large networks, and their application is only limited to small ments we carried out show that our algorithm outperforms case-studies. other techniques and slightly improves results of the original This paper is organized as follows: in the next Section we LM, providing reliable results.
    [Show full text]
  • Principles of Tissue Fractionation
    1. Theoret. Biol. (1964) 6, 33-59 Principles of Tissue Fractionation CHRISTIAN DE DUVE Laboratory of Physiological Chemistry University of Louvain, Belgium and The Rockefeiler Institute, New York, N. Y., U.S.A. (Received 15 April 1963) This paper representsan attempt to develop logically the basic premises that tissuefractionation is : (a) a chemical method to be conducted according to the ground rules which govern chemical fractionation in general; (b) potentially applicable to the separationand characterization of all elements of cellular organization, whether known or unknown, which are not irretrievably lost in the initial grinding of the cells. It is shownthat the approach which best answersthese prerequisites is a purely analytical one, untrammeled by any preconceivedidea of the cyto- logical composition of the isolated fractions, and allowing their bio- chemicalproperties to be expressedas continuous functions of the physical parameterwhich determinesthe behaviour of subcellularcomponents in the fractionation systemchosen, Examples are given which illustrate the appli- cation of density gradient centrifugation in this type of approach, as well as the advantageswhich can be derived from the useof mediaof different composition. The resultsof suchexperiments are expressedin the form of distribution curves of biochemical constituents, as with other fractionation methods such as chromatography or electrophoresis,but with the differencethat the independent variable is related to a property, not of the constituent but of its host-particles. These curves can be taken to represent the mass distribution of the particles themselvesif the constituent is assumedto be homogeneouslydistributed amongstthem (postulateof biochemicalhomo- geneity). This assumptionhas been verified for a number of enzymes,which provide valuable markers to fix the position of their host-particleson the distribution diagrams.
    [Show full text]
  • A Weight-Based Information Filtration Algorithm for Stock-Correlation Networks
    A Weight-based Information Filtration Algorithm for Stock-Correlation Networks Seyed Soheil Hosseini, Nick Wormald ∗, and Tianhai Tian School of Mathematics, Monash University Abstract Several algorithms have been proposed to filter information on a complete graph of corre- lations across stocks to build a stock-correlation network. Among them the planar maximally filtered graph (PMFG) algorithm uses 3n − 6 edges to build a graph whose features include a high frequency of small cliques and a good clustering of stocks. We propose a new algo- rithm which we call proportional degree (PD) to filter information on the complete graph of normalised mutual information (NMI) across stocks. Our results show that the PD algorithm produces a network showing better homogeneity with respect to cliques, as compared to eco- nomic sectoral classification than its PMFG counterpart. We also show that the partition of the PD network obtained through normalised spectral clustering (NSC) agrees better with the NSC of the complete graph than the corresponding one obtained from PMFG. Finally, we show that the clusters in the PD network are more robust with respect to the removal of random sets of edges than those in the PMFG network. Key words— stock-correlation network, PD network, PMFG network, normalised mutual in- formation arXiv:1904.06007v1 [q-fin.ST] 12 Apr 2019 1 Introduction ‘Complex systems’ is the term referring to the study of systems with a significant number of com- ponents in which we want to find out how the relationships between those components affect the behaviour of the system. The study of complex systems includes concepts from various disciplines such as mathematics, statistics, and computer science.
    [Show full text]
  • Community Detection Problem Based on Polarization Measures: an Application to Twitter: the COVID-19 Case in Spain
    mathematics Article Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain Inmaculada Gutiérrez 1,* , Juan Antonio Guevara 1 , Daniel Gómez 1,2 , Javier Castro 1,2 and Rosa Espínola 1,2 1 Faculty of Statistics, Complutense University Puerta de Hierro, 28040 Madrid, Spain; [email protected] (J.A.G.); [email protected] (D.G.); [email protected] (J.C.); [email protected] (R.E.) 2 Instituto de Evaluación Sanitaria, Complutense University, 28040 Madrid, Spain * Correspondence: [email protected] Abstract: In this paper, we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the risk of polarization. Particularly, we are interested in dealing with the problem of taking into account the polarization of nodes in the community detection problem. Adding this type of information to the community detection problem makes it more realistic, as a community is more likely to be defined if the corresponding elements are willing to maintain a peaceful dialogue. The polarization capacity is modeled by a fuzzy measure based on the JDJpol measure of polarization related to two poles. We also present an efficient algorithm for finding groups whose elements are no polarized. Hereafter, we work in a real case. It is a network obtained from Twitter, concerning the political position against the Spanish government taken by Citation: Gutiérrez, I.; Guevara, J.A.; several influential users. We analyze how the partitions obtained change when some additional Gómez, D.; Castro, J.; Espínola, R.
    [Show full text]
  • E Sacred Place and Source of Artistic Inspiration”
    Fujisan World Heritage e sacred place e official and source of guidebook artistic inspiration Connecting the world heritage component assets Fujisan World Heritage Association for Preservation & Utilization, Yamanashi Secretarial Office : Fujisan World Heritage Division, Resident Affairs Department, Yamanashi Prefectural Government Tel : +81-55-223-1316 Fax : +81-55-223-1781 E-mail : [email protected] Date of Issue : 1 January,2018 Translated by : Mt.Fuji Yamanashi Guide-Interpreters Association(FYGIA) Fujisan World Heritage Association for Preservation & Utilization, Yamanashi Creation 1. Creation e erce mountain and source of scenic beauty Fujisan, A Great Road to Worship source of scenic beauty 1The fierce mountain and At registration of Fujisan as a World Cultural Heritage by UNESCO, “Fujigoko (Fuji Five Lakes) ”, that are distributed in an arc at the foot, were included in the list of its component assets. Let’s travel back to the time of foundation of Fujisan. You may feel ineffable emotions to the magnificent scale of nature at Fujisan, which was miraculously born as the fire and water mountain. ■Referred Component assets Lake Saiko, Lake Shojiko and Lake Motosuko ……………………………………………………………………………………………2 Worship from afar 2. Worship from afar Beginning of the worship of the worship 2Beginning In the ancient times that Fujisan was not easily accessible like present days. How people confronted with Fujisan and offered their prayers? If you travel around the ancient sacred places of Fujisan, you will find the figure of Fujisan in deep psychology of the Japanese for nature veneration and mountain worship. Kawaguchi Asama-jinja Shrine, Lake Kawaguchiko ■Referred Component assets and Omuro Sengen-jinja Shrine ……………………………………………………………………………………………9 Fuji-ko 3.
    [Show full text]
  • Mount Fuji Key Facts & Information
    Mount Fuji Key Facts & Information: • Mount Fuji is located on Honshu Island, Japan, near the Pacific Coast. • It is one of Japan’s ‘Three Holy Mountains’, alongside Mount Haku and Mount Tate. • In Japan, Mount Fuji is called ‘Fujisan’. • Mount Fuji is 3,766.24 meters high (12,389.2 feet). • It is the highest mountain in Japan. • The summit of Mount Fuji has a tundra climate and is usually covered in snow. In winter it can be as cold as -21°C, and in summer it reaches around 7°C. • At the summit where the volcano’s crater is, there are eight peaks. • The crater of Mount Fuji is around 500 meters (1,600 feet) wide. Location, History & Geography: • There are three cities that surround Mount Fuji: Gotemba, Fujiyoshida and Fujinomiya. • There are five lakes around Mount Fuji: Lake Kawaguchi, Lake Motosu, Lake Sai, Lake Yamanaka and Lake Shoji. • Mount Fuji is an active composite volcano that last erupted in 1707. It has been classified as being at ‘low risk’ of erupting again, despite recent nearby earthquakes which often signal that an eruption is imminent. • Mount Fuji is 100km southwest of Japan’s capital, Tokyo, and can be seen from the city on a clear day. • Mount Fuji has been classified as a Special Place of Scenic Beauty because of how symmetrical the mountain looks. • Mount Fuji is also on the UNESCO World Heritage List. • The summit of Mount Fuji has always been regarded as sacred. • The first person to climb Mount Fuji was a Buddhist monk in 663 AD.
    [Show full text]