306 research outputs found
Grandchildren of the revolution : sexuality, nation and Frank Ronan
No full textMestrado em Estudos InglesesEsta tese propõe-se a investigar expressões do discurso gay irlandês
contemporâneo na obra do autor irlandês Frank Ronan. O tratamento literário
de temas como a influência da Igreja Católica, a importância da célula familiar
irlandesa, ou a manifestação de posições políticas relacionadas com
nacionalismo e colonialismo nas suas obras será analisado, com vista a
examinar como estes e outros factores moldam a maneira como o discurso
homossexual é construído na república da Irlanda e no trabalho de Frank
Ronan em particular. Também será dada atenção a estereótipos nacionais e o
seu efeito na escrita de Frank Ronan.
ABSTRACT: This dissertation proposes an investigation of expressions of the contemporary
Irish gay discourse in the fiction of Irish author Frank Ronan. The literary
treatment of themes such as the influence of the Catholic Church, the
importance of the Irish family cell, or the manifestation of political views,
concerning nationalism and colonialism in the novels will be analysed, in order
to study how these and other factors shape the way that homosexual discourse
is constructed in the Republic of Ireland and in the work of Frank Ronan in
particular. Attention will also be given to Irish national stereotypes, and their
effect on Ronan’s writing
Children and Disasters: A tribute to Professor Kevin Ronan
No full text(c) The Author/sIn 1997, Professor Kevin Ronan published a paper in the first ever edition of the Australasian Journal of Disaster and Trauma Studies, titled “The Effects of a “Benign” Disaster: Symptoms of Post-traumatic Stress in Children Following a Series of Volcanic Eruptions”. Over the next 23 years, Kevin and his many colleagues pursued aspects of children and disasters to both improve practice and advance scholarship in this area. In March 2020 we were saddened by the untimely passing of Kevin. As a tribute to Professor Ronan this special issue of the Australasian Journal of Disaster and Trauma Studies brings together accounts of current research and practice initiatives inspired by, building upon, and directly influenced by Professor Ronan’s work
Privilege and Property. Essays on the History of Copyright
No full textCopyright law is the site of significant contemporary controversy. In recent years copyright history has transformed as a subject from being one of interest to a few books historians to the focus of sustained historical investigation attracting the attention of scholars from across the humanities. This book comprises a collection of essays on copyright history by leading experts drawn from a range of countries and disciplinary perspectives.
Covering the period from 1450 to 1900, these essays engage with a number of related themes. The first considers the general movement, from the sixteenth century onwards, from privilege to property-based conceptions of copyright protection. The second addresses the relationship between the protection provided for literary and print materials and that provided for other forms of cultural production. The third concerns the significance and relevance of these various histories in shaping and informing contemporary policy and academic practice.
Essays include:
0. The History of Copyright History, by Kretschmer, Deazley & Bently;
1. From Gunpowder to Print: The Common Origins of Copyright and Patent, by Joanna Kostylo;
2. A Mongrel of early modern copyright: Scotland in European Persepctive, by Alastair Mann;
3. The Public Sphere and the Emergence of Copyright: Areopagitica, the Stationers’ Company, and the Statute of Anne, by Mark Rose;
4. Early American Printing Privileges: the Ambivalent Origins of Authors’ Copyright in America, by Oren Bracha;
5. Author and Work in the French Print Privileges System: Some Milestones, by Laurent Pfister;
6. A Venetian Experiment on Perpetual Copyright, by Maurizio Borghi;
7. Les formalités son mortes, vive les formalities! Copyright formalities in nineteenth century Europe, by Stef van Gompel;
8. The Berlin Publisher Friedrich Nicolai and the reprinting sections of the Prussian Statute Book of 1794, by Friedemann Kawohl;
9. Nineteenth Century Controversies relating to the protection of Artistic Property in France, by Frédéric Rideau;
10. Maps, Views and Ornament. Visualising Property in Art and Law: The Case of pre-modern France, by Katie Scott;
11. Breaking the Mould? The Radical Nature of the Fine Art Copyright Bill 1862, by Ronan Deazley;
12. ‘Neither bolt nor chain, iron safe nor private watchman, can prevent the theft of words’: The birth of the performing right in Britain, by Isabella Alexander;
13. The Return of the Commons: Copyright History as a Common Source, by Karl-Nikolaus Peifer;
14. The Significance of Copyright History for the Publishing History and Historians, by John Feather;
15. Metaphors of Intellectual Property, by William St Clair.
The volume is a companion to the digital archive Primary Sources on Copyright (1450-1900), funded by the UK Arts and Humanities Research Council (AHRC): www.copyrighthistory.or
Progress and Distress on the Stratford Estate in Clare during the Eighteen Forties
No full textIn the late 1980s and early 1990s, the author acquired about 30,000 letters written mainly in the 1840s. These pertained to estates throughout Ireland managed by James Robert Stewart and Joseph Kincaid, hereafter denoted SK. Until the letters - called the SK correspondence in what follows - became the author’s property, they had not seen light of day since the 1840s. Addressed mainly to the SK office in Dublin, they were written mainly by landlords, tenants, the partners in SK, local agents, etc. After about 200 years in operation as a land agency, the firm in which members of the Stewart family were the principal partners - Messrs J. R. Stewart & Son(s) from the mid-1880s onwards -- ceased business in the mid-1980s. Since 1994 the author has been researching the SK correspondence of the 1840s. It gives many new insights into economic and social conditions in Ireland during the decade of the great famine, and into the operation of Ireland’s most important land agency during those years. It is intended ultimately to publish details on several of the estates managed by SK in book form. The proposed title is Landlords, Tenants, Famine: Business of an Irish Land Agency in the 1840s, a draft of which has now been completed. A majority of the letters in the larger study from which the present article is drawn are on themes some of which one might expect - rents, distraint (seizure of assets in lieu of rent) ; ‘voluntary’ surrender of land in return for ‘compensation’ upon peacefully quitting; formal ejectment (a matter of last resort on estates managed by SK); landlord-assisted emigration (on a scale much more extensive than most historians of Ireland in the 1840s appear to believe); petitions from tenants; complaints by tenants, both about other tenants and local agents; major works of improvement (on almost all of the estates managed by SK); applications by SK, on behalf of proprietors, for government loans to finance improvements; recommendations of agricultural advisers hired by SK, ete. Thus, most of the SK correspondence is about aspects of estate management. It seems, in the 1840s, that the only estate in Clare managed by SK was that of the elderly Col. Stratford. Although the files on the relatively small Stratford estate are much less extensive than those on some of the estates investigated in detail in the draft of Landlords, Tenants, Famine, they do refer to most of the core aspects of estate management mentioned above. But in the case of the Clare estate, the material on some of those themes is extremely thin.
Expected public and private benefits of embedding farm business performance systems in the Australian and New Zealand dairy industries
No full textDairy industry organizations, universities and government agencies are variously involved in embedding web-based, standardized farm business performance systems in the Australian and New Zealand industries. The spectrum of involvement prompts an exploration of demand drivers and expectations of benefits, public and private. Inclusion of South Australian dairy businesses in a web data system as part of implementing the South Australian dairy industry strategic plan is discussed as an example where public and private benefits are expected. To the extent that adoption of the web as a data management platform is an aid to dialogue in the public-private partnership of industry development more detailed research about the systems and their benefits to stakeholders is merited.Farm Management,
A Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET-GEE)
No full textA Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET)
This is a Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET) developed by the Surface Dynamics and Modeling Lab at the University of Alabama that calculates flood depth using a flood extent layer and a digital elevation model. This research is made possible by the CyberSeed Program at the University of Alabama. Project name: WaterServ: A Cyberinfrastructure for Analysis, Visualization and Sharing of Hydrological Data.
Please see the associated publications:
1. Peter, B.G., Cohen, S., Lucey, R., Munasinghe, D., Raney, A. and Brakenridge, G.R., 2020. Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for rapid and large scale flood analysis. IEEE Geoscience and Remote Sensing Letters, 19, pp.1-5.
https://ieeexplore.ieee.org/abstract/document/9242297
2. Cohen, S., Peter, B.G., Haag, A., Munasinghe, D., Moragoda, N., Narayanan, A. and May, S., 2022. Sensitivity of remote sensing floodwater depth calculation to boundary filtering and digital elevation model selections. Remote Sensing, 14(21), p.5313.
https://www.mdpi.com/2072-4292/14/21/5313>https://www.mdpi.com/2072-4292/14/21/5313
GitHub Repository (ArcMap and QGIS implementations): https://github.com/csdms-contrib/fwdet
3. Cohen, S., A. Raney, D. Munasinghe, J.D. Loftis J, A. Molthan, J. Bell, L. Rogers, J. Galantowicz, G.R. Brakenridge7, A.J. Kettner, Y. Huang, Y. Tsang, (2019). The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote Sensing Analysis of Coastal Flooding. Natural Hazards and Earth System Sciences, 19, 2053–2065. https://doi.org/10.5194/nhess-19-2053-2019
4. Cohen, S., G. R. Brakenridge, A. Kettner, B. Bates, J. Nelson, R. McDonald, Y. Huang, D. Munasinghe, and J. Zhang (2018), Estimating Floodwater Depths from Flood Inundation Maps and Topography, Journal of the American Water Resources Association, 54 (4), 847–858. https://doi.org/10.1111/1752-1688.12609
Sample products and data availability:
https://sdml.ua.edu/models/fwdet/
https://sdml.ua.edu/michigan-flood-may-2020/
https://cartoscience.users.earthengine.app/view/fwdet-gee-mi
https://alabama.app.box.com/s/31p8pdh6ngwqnbcgzlhyk2gkbsd2elq0
GEE implementation output: fwdet_gee_brazos.tif
ArcMap implementation output (see Cohen et al. 2019): fwdet_v2_brazos.tif
iRIC validation layer (see Nelson et al. 2010): iric_brazos_hydraulic_model_validation.tif
Brazos River inundation polygon access in GEE: var brazos = ee.FeatureCollection('users/cartoscience/FwDET-GEE-Public/Brazos_River_Inundation_2016')
Nelson, J.M., Shimizu, Y., Takebayashi, H. and McDonald, R.R., 2010. The international river interface cooperative: public domain software for river modeling. In 2nd Joint Federal Interagency Conference, Las Vegas, June (Vol. 27).
Google Earth Engine Code
/* ----------------------------------------------------------------------------------------------------------------------
# FwDET-GEE calculates floodwater depth from a floodwater extent layer and a DEM
Authors: Brad G. Peter, Sagy Cohen, Ronan Lucey, Dinuke Munasinghe, Austin Raney
Emails: [email protected], [email protected], [email protected], [email protected], [email protected]
Organizations: BP, SC, DM, AR - University of Alabama; RL - University of Alabama in Huntsville
Last Modified: 10/08/2020
To cite this code use:
Peter, Brad; Cohen, Sagy; Lucey, Ronan; Munasinghe, Dinuke; Raney, Austin, 2020, "A Google Earth Engine implementation
of the Floodwater Depth Estimation Tool (FwDET-GEE)", https://doi.org/10.7910/DVN/JQ4BCN, Harvard Dataverse, V2
-------------------------------------------------------------------------------------------------------------------------
This is a Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDETv2.0) [1] developed by the
Surface Dynamics and Modeling Lab at the University of Alabama that calculates flood depth using a flood extent layer
and a digital elevation model. This research is made possible by the CyberSeed Program at the University of Alabama.
Project name: WaterServ: A Cyberinfrastructure for Analysis, Visualization and Sharing of Hydrological Data.
GitHub Repository (ArcMap and QGIS implementations): https://github.com/csdms-contrib/fwdet
-------------------------------------------------------------------------------------------------------------------------
How to run this code with your flood extent GEE asset:
User of this script will need to update path to flood extent (line 32 or 33) and select from the processing options.
Available DEM options (1) are USGS/NED (U.S.) and USGS/SRTMGL1_003 (global). Other options include (2) running the elevation
outlier filtering algorithm, (3) adding water body data to the inundation extent, (4) add a water body data layer uploaded by
the user rather than using the JRC global surface water data, (5) masking out regular water body data, (6) masking out 0 m
depths, (7) choosing whether or not to export, (8) exporting additional data layers, and (9) setting an export file name.
The simpleVis option (10) bypasses the time consuming processes and is meant for visualization only; set this option to false
to complete the entire process and enable exporting.
-------------------------------------------------------------------------------------------------------------------------
••••••••••••••••••••••••••••••••••••••••••• USER OPTIONS ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••
Load flood extent layer | Flood extent layer must be uploaded to GEE first as an asset. If the flood extent is a
shapefile, upload as a FeatureCollection; otherwise, if the flood extent layer is a raster, upload it as an image.
A raster layer may be required if the flood extent is a highly complex geometry -------------------------------------- */
var flood = ee.FeatureCollection('users/username/folder/flood_extent') // comment out this line if using an Image
// var flood = ee.Image('users/username/folder/flood_extent') // comment out this line if using a FeatureCollection
var waterExtent = ee.FeatureCollection('users/username/folder/water_extent') // *OPTIONAL* comment out this line if using an Image
// var waterExtent = ee.Image('users/username/folder/water_extent') // *OPTIONAL* comment out this line if using a FeatureCollection
// Processing options - refer to the directions above
/*1*/ var demSource = 'USGS/NED' // 'USGS/NED' or 'USGS/SRTMGL1_003'
/*2*/ var outlierTest = 'TRUE' // 'TRUE' (default) or 'FALSE'
/*3*/ var addWater = 'TRUE' // 'TRUE' (default) or 'FALSE'
/*4*/ var userWater = 'FALSE' // 'TRUE' or 'FALSE' (default)
/*5*/ var maskWater = 'FALSE' // 'TRUE' or 'FALSE' (default)
/*6*/ var maskZero = 'FALSE' // 'TRUE' or 'FALSE' (default)
/*7*/ var exportLayer = 'TRUE' // 'TRUE' (default) or 'FALSE'
/*8*/ var exportAll = 'FALSE' // 'TRUE' or 'FALSE' (default)
/*9*/ var outputName = 'FwDET_GEE' // text string for naming export file
/*10*/ var simpleVis = 'FALSE' // 'TRUE' or 'FALSE' (default)
// ••••••••••••••••••••••••••••••••• NO USER INPUT BEYOND THIS POINT ••••••••••••••••••••••••••••••••••••••••••••••••••••
// Create buffer around flood area to use for clipping other layers
var area = flood.geometry().bounds().buffer(1000).bounds()
// Load DEM and grab projection info
var dem = ee.Image(demSource).select('elevation').clip(area) // [2,3]
var projection = dem.projection()
var resolution = projection.nominalScale().getInfo()
// Load global surface water layer
var jrc = ee.Image('JRC/GSW1_1/GlobalSurfaceWater').select('occurrence').clip(area) // [4]
var water_image = jrc
// User uploaded flood extent layer
// Identify if a raster or vector layer is being used and proceed with appropriate process
if ( flood.name() == 'FeatureCollection' ) {
var addProperty = function(feature) {
return feature.set('val',0);
};
var flood_image = flood.map(addProperty).reduceToImage(['val'],ee.Reducer.first())
.rename('flood')
} else {
var flood_image = flood.multiply(0)
}
// Optional user uploaded water extent layer
if ( userWater == 'TRUE' ) {
// Identify if a raster or vector layer is being used and proceed with appropriate process
if ( waterExtent.name() == 'FeatureCollection' ) {
var addProperty = function(feature) {
return feature.set('val',0);
};
var water_image = waterExtent.map(addProperty).reduceToImage(['val'],ee.Reducer.first())
.rename('flood')
} else {
var water_image = waterExtent.multiply(0)
}
}
// Add water bodies to flood extent if 'TRUE' is selected
if ( addWater == 'TRUE' ) {
var w = water_image.reproject(projection)
var waterFill = flood_image.mask().where(w.gt(0),1)
flood_image = waterFill.updateMask(waterFill.eq(1)).multiply(0)
}
// Change processing options if 'TRUE' is selected
if ( simpleVis == 'FALSE' ) {
flood_image = flood_image.reproject(projection)
} else {
outlierTest = 'FALSE'
exportLayer = 'FALSE'
}
// Run the outlier filtering process if 'TRUE' is selected
if ( outlierTest == 'TRUE' ) {
// Outlier detection and filling on complete DEM using the modified z-score and a median filter [5]
var kernel = ee.Kernel.fixed(3,3,[[1,1,1],[1,1,1],[1,1,1]])
var kernel_weighted = ee.Kernel.fixed(3,3,[[1,1,1],[1,0,1],[1,1,1]])
var median = dem.focal_median({kernel:kernel}).reproject(projection)
var median_weighted = dem.focal_median({kernel:kernel_weighted}).reproject(projection)
var diff = dem.subtract(median)
var mzscore = diff.multiply(0.6745).divide(diff.abs().focal_median({kernel:kernel}).reproject(projection))
var fillDEM = dem.where(mzscore.gt(3.5),median_weighted)
// Outlier detection and filling on the flood extent border pixels
var expand = flood_image.focal_max({kernel: ee.Kernel.square({
radius: projection.nominalScale(),
units: 'meters'
})}).reproject(projection)
var demMask = fillDEM.updateMask(flood_image.mask().eq(0))
var boundary = demMask.add(expand)
var medianBoundary = boundary.focal_median({kernel:kernel}).reproject(projection)
var medianWeightedBoundary = boundary.focal_median({kernel:kernel_weighted}).reproject(projection)
var diffBoundary = boundary.subtract(medianBoundary)
var mzscoreBoundary = diffBoundary.multiply(0.6745).divide(diffBoundary.abs().focal_median({kernel:kernel}).reproject(projection))
var fill = fillDEM.where(mzscoreBoundary.gt(3.5),medianWeightedBoundary)
} else {
var fill = dem
}
// cumulativeCost floodwater surface elevation model (adaptation of the cost allocation method from FwDETv2.0)
var mod = fill.updateMask(flood_image.mask().eq(0))
var source = mod.mask()
var val = 10000
var push = 5000
var cost0 = ee.Image(val).where(source,0).cumulativeCost(source,push)
var cost1 = ee.Image(val).where(source,1).cumulativeCost(source,push)
var cost2 = mod.unmask(val).cumulativeCost(source,push)
var costFill = cost2.subtract(cost0).divide(cost1.subtract(cost0))
var costSurface = mod.unmask(0).add(costFill)
// Interpolation method courtesy of Matt Hancher (Earth Engine Co-Founder) posted to the GEE developer forums
// https://groups.google.com/forum/#!forum/google-earth-engine-developers
// Kernel size for low-pass filter
var boxcar = ee.Kernel.square({
radius: 3, units: 'pixels', normalize: true
});
// Floodwater depth calculation and smoothing using a low-pass filter
var costDepth = costSurface.subtract(fill)
.rename('FwDET_GEE')
.convolve(boxcar)
.reproject(projection)
.updateMask(flood_image.eq(0))
var costDepthFilter = costDepth.where(costDepth.lt(0),0)
// Mask out regular water bodies if 'TRUE' is selected
if ( maskWater === 'TRUE' ) {
var w = jrc.reproject(projection)
costDepthFilter = costDepthFilter.updateMask(w.mask().eq(0))
}
// Mask out zero values if 'TRUE' is selected
if ( maskZero === 'TRUE' ) {
costDepthFilter = costDepthFilter.updateMask(costDepthFilter.neq(0))
}
// Add flood depth to console
Map.clear()
Map.setOptions('HYBRID')
Map.centerObject(flood)
// Add message to user
var message = ui.Panel({
layout: ui.Panel.Layout.flow('vertical'),
style: {position: 'bottom-left', border: '1px solid gray', padding: '2px'}
})
message.widgets().set(0,ui.Label('Check tasks tab for export'));
Map.add(message);
// Change options for visualization sample
if ( simpleVis == 'TRUE' ) {
var histOptions = {
title: 'Depth (m)',
fontSize: 11,
legend: {position: 'none'},
series: {0: {color: '7100AA'}}
};
var histogram = ui.Chart.image.histogram({
image: costDepthFilter.updateMask(costDepthFilter.neq(0)),
region: area,
scale: resolution*10
}).setOptions(histOptions)
Map.addLayer(costDepthFilter,{},'FwDET GEE',true)
message.widgets().set(0,ui.Label("set simpleVis to 'FALSE' to export layers"))
message.widgets().set(1,histogram)
} else {
Map.addLayer(flood_image,{},'flood extent',true)
Map.addLayer(costDepthFilter,{},'FwDET GEE',false)
}
// Export function
var exportFunc = function(i,n) {
return Export.image.toDrive({
image: i,
description: outputName+n,
fileNamePrefix: outputName+n,
maxPixels: 1e13,
scale: resolution,
region: area
})
}
// Export output if 'TRUE' is selected
if ( exportLayer === 'TRUE' ) {
exportFunc(costDepthFilter, '_FwDET')
// Export all layers if 'TRUE' is selected
if ( exportAll == 'TRUE' ) {
exportFunc(costSurface, '_costSurface')
exportFunc(dem, '_dem')
exportFunc(fill, '_demFill')
}
}
/* ----------------------------------------------------------------------------------------------------------------------
// Citations
// [1] Cohen, S., A. Raney, D. Munasinghe, J.D. Loftis J, A. Molthan, J. Bell, L. Rogers, J. Galantowicz,
// G.R. Brakenridge7, A.J. Kettner, Y. Huang, Y. Tsang, (2019). The Floodwater Depth Estimation Tool (FwDET v2.0)
// for Improved Remote Sensing Analysis of Coastal Flooding. Natural Hazards and Earth System Sciences, 19, 2053–2065.
// https://doi.org/10.5194/nhess-19-2053-2019
// [2] Gesch, D., Oimoen, M., Greenlee, S., Nelson, C., Steuck, M. and Tyler, D., 2002. The national elevation dataset.
// Photogrammetric engineering and remote sensing, 68(1), pp.5-32.
// [3] Farr, T.G., Rosen, P.A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E.,
// Roth, L. and Seal, D., 2007. The shuttle radar topography mission. Reviews of geophysics, 45(2).
// [4] Pekel, J.F., Cottam, A., Gorelick, N. and Belward, A.S., 2016. High-resolution mapping of global surface
// water and its long-term changes. Nature, 540(7633), pp.418-422.
// [5] Iglewicz, B. and Hoaglin, D.C., 1993. How to detect and handle outliers (Vol. 16). Asq Press.
---------------------------------------------------------------------------------------------------------------------- */
</pre
Assessing Time-Weighted Dynamic Time Warping as a Method for Land Cover Classification Utilizing NASA Satellite Imagery
No full texthttps://louis.uah.edu/vbs-posters/1074/thumbnail.jp
A comparison of techniques for estimating NDVI for agricultural intervention impact assessment
No full textIn the context of global environmental change, food security is a major concern for Nepal. Agricultural interventions have been performed in Nepal with a goal of increasing crop productivity to combat food insecurity. In this study, we compare two techniques for estimating NDVI, serving as a proxy for agricultural productivity, over fields in western Nepal - a Multi-Linear Regression approach and a Random Forest approach. Assessment of agricultural productivity is important for understanding the effectiveness of agricultural interventions. The methodology utilizes space-borne remote sensing and surface meteorology datasets to address three research questions: 1) can these datasets be utilized along with statistical and machine learning models to predict single time values of NDVI, 2) predict time series values of NDVI and, 3) can the resulting NDVI predictions be used to assess the impact of agricultural interventions? Multi-linear regression and Random Forest models were constructed to predict future values of NDVI for both one time step and as a time series. For a single time step NDVI prediction, Random Forest (RF) models showed better overall performance ( = 0.67) compared to the Multiple Linear Regression (MLR) model ( = 0.15). While the RF model is less skillful at time series prediction ( \textless 0.5), it performs better compared to a MLR model making similar predictions. A framework for assessment of impact of interventions was developed, and the methodology was tested with the results of the RF time series prediction. Preliminary investigations show that Artificial Neural Networks (ANN) have the potential to improve upon the results obtained from RF and MLR models for NDVI prediction
A Study on the Fashion Design of Ronan Bouroullec’s Felt-pen Drawing by Applying the Formality : Focusing on cutting tape embroidery
No full text패션은 다양한 분야와의 접목을 통해 표현 영역을 점차 확대하고 있으며, 특히 미술은 중요한 영감의 원천이 되어왔다. 드로잉은 작가의 생각을 구체화하는 발상의 과정인 동시에 직관을 드러내는 창조 행위의 시작으로서, 선으로 그리는 스케치의 의미를 넘어 작가의 개성이 담긴 하나의 작품으로써 평가되기도 한다. 하지만 기존의 패션디자인 연구에서는 드로잉을 접목한 사례가 많지 않다.
이에 본 연구는 로낭 부훌렉 드로잉 작품 중 펠트펜 드로잉에 나타나는 조형성을 응용한 패션디자인에 관하여 연구하였다. 로낭 부훌렉은 유기적인 현대 디자인의 새로운 방향을 모색한 작가로, 그의 드로잉 작업은 독자적인 예술적 가치를 지닌 작품으로 평가받고 있다. 본 연구에서는 이러한 로낭 부훌렉 펠트펜 드로잉의 부드럽고 유기적인 선의 흐름, 반복과 겹침에 의한 시각적 질감을 촉각적 질감으로 표현하기 위해 컷 테이프 자수 기법을 디자인에 접목하였다.
본 연구의 목적은 로낭 부훌렉 펠트펜 드로잉을 컷 테이프 자수 기법을 중심으로 패션디자인에 응용함으로써, 패션의 모티프로서 드로잉의 가치를 재발견하고 패션디자인의 표현영역을 확대하는 데에 있다.
본 연구의 내용 및 방법은 다음과 같다. 이론적 배경에서는 로낭 부훌렉의 작품세계와 펠트펜 드로잉에 관하여 살펴보고, 로낭 부훌렉 펠트펜 드로잉의 조형적 특성을 분석한다. 또한 표현 기법으로써 선택한 테이프 자수 기법의 정의와 종류, 이를 응용한 패션디자인 사례를 분석한다. 분석한 이론적 배경을 토대로 로낭 부훌렉 펠트펜 드로잉의 조형성을 응용한 실물 작품 5벌을 제작한다.
본 연구를 통해 도출된 결론은 다음과 같다.
첫째, 작품의 모티프로서 로낭 부훌렉의 펠트펜 드로잉은 곡선과 직선의 혼합과굵기의 다양한 변화, 반복된 선의 방향성으로 인해 자유롭고 유기적인 선의 흐름을 표현하기에 적합하였다.
둘째, 로낭 부훌렉 드로잉을 테이프 자수 기법으로 표현한 결과, 테이프의 반복과 겹침에 의해 요철감과 결을 형성함으로써 드로잉에 나타난 시각적 질감을 촉각적 질감으로 전환하기에 효과적이었다. 또한 바이어스 컷 테이프의 중첩에 의한 연속면은 밀도 변화에 따라 섬세한 드로잉의 결의 이미지와 볼륨감을 표현하기에 적합하였다.
셋째, 작품의 소재에 있어서 투시성이 있는 반투명의 오간자는 로낭 부훌렉의 펠트펜 드로잉에 나타난 투명감과 중첩의 효과를 부각하기에 적합하였다.
넷째, 로낭 부훌렉의 펠트펜 드로잉에 나타난 주된 색조인 ‘light clear&apos;를 작품에 적용한 결과, 로낭 부훌렉 드로잉에서 나타나는 부드럽고 맑은 이미지를 보다 강조할 수 있었다.
본 연구는 로낭 부훌렉의 펠트펜 드로잉 작품에 나타나는 조형적 특성을 테이프 자수 기법을 통해 패션디자인에 응용하고자 하였다. 이를 통해 패션의 모티프로서 드로잉 작품이 유기적인 선의 흐름을 창출할 수 있음을 확인할 수 있었으며, 컷 테이프 자수 기법이 시각적 질감을 촉각적 질감으로 전환하기에 효과적인 기법임을 확인할 수 있었다. 본 연구를 통해 드로잉을 접목한 다양한 시도가 보다 확대되길 기대한다.
;Fashion has gradually expanded its expressiveness through its interlinking with various fields, and art in particular has been an important source of inspiration. Drawing is the beginning of an act of creativity that embodies the author&apos;s ideas and also reveals his intuition, and is considered to be a work of the writer&apos;s individuality beyond the meaning of a line sketch. However, not many existing fashion design studies have incorporated drawing.
In this study, we studied fashion design that applied the formative properties of felt-pen drawing among Ronan Bouroullec drawing works. Ronan Bouroullec is an author who has sought a new direction in organic modern design, and his drawing work is regarded as a work of independent artistic value. In this study, a cut tape embroidery technique was incorporated into the design to express the smooth and organic flow of lines in these Ronan Bouroullec felt-tongued visual texture by repetition and overlap as tactile
The purpose of this study is to rediscover the value of drawing as a fashion motif and expand the area of expression in fashion design by applying Ronan Bouroullec felt-pen drawing to fashion design with a focus on cut tape embroidery technique.
The content and methods of this study are as follows. In the theoretical background, we examine the work world of Ronan Bouroullec and the felt-pen drawing, and analyze the modeling characteristics of Ronan Bouroullec felt-pen drawing. It also analyzes the definition and type of tape embroidery technique selected as an expression technique, and the fashion design case in which it is applied. Based on the theoretical background analyzed, five real-life works that apply the formative nature of Ronan Bouroullec felt-pen drawing will be produced.
The conclusions drawn from this study are as follows:
First, the felt-pen drawing of Ronan Bouroullec as the motif of the work was suitable to express the flow of free and organic lines due to the mixture of curves and straight lines, various changes in thickness, and the direction of repeated lines.
Second, as a result of expressing Ronan Bouroullec drawing with tape embroidery technique, it was effective to convert the visual texture shown in drawing into tactile texture by forming bumps and cones by repetition and overlap of tape. In particular, continuous surfaces by bias cut tapes were suitable for expressing resolution images and volumetric feelings of fine drawing with varying density.
Third, the translucent Oganza, which were visible in the subject matter of the work, was suitable to highlight the effect of transparency and overlay shown in the felt-pen drawing of Ronan Bouroullec.
Fourth, as a result of applying light clear, the primary shade of color in the felt-pen drawing of Ronan Bouroullec, to the work, the soft and clear image of Ronan Bouroullec was more emphasized.
This study intended to apply the plastic characteristics of Ronan Bouroullec&apos;s felt-pen drawing work to fashion design through tape embroidery techniques. This confirmed that drawing work as a motif of fashion can create an organic stream of lines, and that cutting tape embroidery technique is an effective technique for converting visual texture into tactile texture. It is hoped that the various attempts to graft drawing will be further expanded through this study.Ⅰ. 서론 1
A. 연구의 목적 1
B. 연구 방법과 내용 2
Ⅱ. 이론적 배경 3
A. 로낭 부훌렉의 드로잉에 관한 고찰 3
1. 로낭 부훌렉의 작품세계와 펠트펜 드로잉 3
2. 로낭 부훌렉 펠트펜 드로잉의 조형적 특성 17
B. 테이프 자수에 관한 고찰 26
1. 테이프 자수 기법의 종류 27
2. 컷 테이프 자수 기법을 활용한 패션디자인 사례 32
Ⅲ. 작품 제작 및 해설 37
A. 작품 제작 의도 및 방법 37
B. 작품 및 해설 41
Ⅳ. 결론 83
참고문헌 85
ABSTRACT 8
Evaluating a New Impact Assessment Method for Agricultural Productivity Treatments in Nepal Using Machine Learning and Space-Borne Data
No full texthttps://louis.uah.edu/vbs-posters/1181/thumbnail.jp
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