Fashion is a complex social and economic phenomenon that is difficult to define. It involves changes in styles and trends in areas like clothing, but also extends to other domains like music, art, and architecture. While fashion has ancient roots, it developed further with the rise of capitalism in medieval Europe, when changes in clothing styles became more rapid and cultivated for their own sake. Fashion operates within economic and social systems and is shaped by both commercial interests as well as creative forces. It serves as a means of social identification and communication of personal identity. The Indian fashion industry has grown significantly in recent decades due to factors like rising incomes, globalization, and the influence of Bollywood. Fashion in Delhi is strongly status-conscious and
All of these slideshows are interactive and that's why they look jumbled up. They really are cool to look at and study so I will email the original file if someone wants it. All I ask is to not make any changes to it.
it`s easy to get full marks in exam by completing question of this question bank!!try it get a full scope to be the topper of the class!!@@ if u like it very much then u can share it ! to any body else who need helps in this subject:: THNX FOR SEEING MY PROJECT!(my email::ansumanpanigrahi321@gmail.com) mail me if u want further more chapter for help~!! with images and lot`s of animation
Fashion is a dynamic and ever-evolving form of self-expression that encompasses clothing, accessories, and personal style choices. It reflects cultural, societal, and individual trends, allowing people to showcase their personality, creativity, and identity through what they wear. Fashion is not just about following trends but also about making unique statements and feeling confident in one's appearance. It is a powerful means of communication, enabling individuals to convey messages, cultural affiliations, and even social or political statements through their clothing choices. Fashion is an art form that constantly evolves, influenced by designers, celebrities, social media, and historical and cultural influences, making it a vibrant and integral part of our daily lives.
Fashion is an ever-changing and dynamic form of self-expression that has woven its way through the fabric of human history. From ancient civilizations to the modern era, clothing and accessories have played a crucial role in reflecting societal values, cultural influences, and individual identities. This article delves into the rich tapestry of fashion, exploring its evolution over the centuries and the impact it has on our lives.
The Birth of Fashion
The roots of fashion can be traced back to the earliest human societies, where clothing served a functional purpose to protect individuals from the elements. However, as civilizations developed, so did the desire for personal adornment and the need to distinguish oneself from others. The ancient Egyptians, for example, were pioneers in the world of fashion, utilizing intricate jewelry, ornate headdresses, and flowing garments to signify status and power.
Medieval Elegance
The Middle Ages witnessed the emergence of elaborate garments that reflected the hierarchical structure of society. Nobility adorned themselves with luxurious fabrics, such as silk and velvet, adorned with intricate embroidery and jewels. The Renaissance era further fueled the evolution of fashion, with an emphasis on individualism and the resurgence of classical aesthetics.
The Birth of Haute Couture
The 19th century marked a significant turning point in the world of fashion with the rise of haute couture in Paris. Designers like Charles Frederick Worth and Paul Poiret became household names, revolutionizing the industry by creating custom-made garments for the elite. This era laid the foundation for the modern fashion system, introducing seasonal collections and establishing Paris as the fashion capital of the world.
The Roaring Twenties and Art Deco Influence
The 1920s brought about a seismic shift in fashion, symbolizing the liberation of women from restrictive corsets and embracing a more relaxed and androgynous style. The flapper dress, characterized by its loose silhouette and embellishments, became a symbol of the era's newfound freedom. The Art Deco movement also influenced fashion, with geometric shapes and bold patterns dominating the design landscape.
World War II and Utility Fashion
The tumultuous period of World War II had a profound impact on fashion, leading to the emergence of utility clothing. Rationing and practicality took precedence, influencing the design of garments with simpler lines and minimal embellishments. This era marked a departure from extravagance and a focus on functionality, reflecting the somber mood of the times.
Post-War Glamour and the Rise of Ready-to-Wear
The post-war period witnessed a resurgence of glamour and a departure from the utilitarian styles of the previous decade. Christian Dior's "New Look," introduced in 1947, revolutionized fashion with its emphasis on a cinched waist and voluminous skirts, bringing a sense of opulence back to clothing. Simultaneously, the rise .
All of these slideshows are interactive and that's why they look jumbled up. They really are cool to look at and study so I will email the original file if someone wants it. All I ask is to not make any changes to it.
it`s easy to get full marks in exam by completing question of this question bank!!try it get a full scope to be the topper of the class!!@@ if u like it very much then u can share it ! to any body else who need helps in this subject:: THNX FOR SEEING MY PROJECT!(my email::ansumanpanigrahi321@gmail.com) mail me if u want further more chapter for help~!! with images and lot`s of animation
Fashion is a dynamic and ever-evolving form of self-expression that encompasses clothing, accessories, and personal style choices. It reflects cultural, societal, and individual trends, allowing people to showcase their personality, creativity, and identity through what they wear. Fashion is not just about following trends but also about making unique statements and feeling confident in one's appearance. It is a powerful means of communication, enabling individuals to convey messages, cultural affiliations, and even social or political statements through their clothing choices. Fashion is an art form that constantly evolves, influenced by designers, celebrities, social media, and historical and cultural influences, making it a vibrant and integral part of our daily lives.
Fashion is an ever-changing and dynamic form of self-expression that has woven its way through the fabric of human history. From ancient civilizations to the modern era, clothing and accessories have played a crucial role in reflecting societal values, cultural influences, and individual identities. This article delves into the rich tapestry of fashion, exploring its evolution over the centuries and the impact it has on our lives.
The Birth of Fashion
The roots of fashion can be traced back to the earliest human societies, where clothing served a functional purpose to protect individuals from the elements. However, as civilizations developed, so did the desire for personal adornment and the need to distinguish oneself from others. The ancient Egyptians, for example, were pioneers in the world of fashion, utilizing intricate jewelry, ornate headdresses, and flowing garments to signify status and power.
Medieval Elegance
The Middle Ages witnessed the emergence of elaborate garments that reflected the hierarchical structure of society. Nobility adorned themselves with luxurious fabrics, such as silk and velvet, adorned with intricate embroidery and jewels. The Renaissance era further fueled the evolution of fashion, with an emphasis on individualism and the resurgence of classical aesthetics.
The Birth of Haute Couture
The 19th century marked a significant turning point in the world of fashion with the rise of haute couture in Paris. Designers like Charles Frederick Worth and Paul Poiret became household names, revolutionizing the industry by creating custom-made garments for the elite. This era laid the foundation for the modern fashion system, introducing seasonal collections and establishing Paris as the fashion capital of the world.
The Roaring Twenties and Art Deco Influence
The 1920s brought about a seismic shift in fashion, symbolizing the liberation of women from restrictive corsets and embracing a more relaxed and androgynous style. The flapper dress, characterized by its loose silhouette and embellishments, became a symbol of the era's newfound freedom. The Art Deco movement also influenced fashion, with geometric shapes and bold patterns dominating the design landscape.
World War II and Utility Fashion
The tumultuous period of World War II had a profound impact on fashion, leading to the emergence of utility clothing. Rationing and practicality took precedence, influencing the design of garments with simpler lines and minimal embellishments. This era marked a departure from extravagance and a focus on functionality, reflecting the somber mood of the times.
Post-War Glamour and the Rise of Ready-to-Wear
The post-war period witnessed a resurgence of glamour and a departure from the utilitarian styles of the previous decade. Christian Dior's "New Look," introduced in 1947, revolutionized fashion with its emphasis on a cinched waist and voluminous skirts, bringing a sense of opulence back to clothing. Simultaneously, the rise .
Fashion Trends Through the Decades, Bold & Bae.pdfboldandbaeseo
Today, we embark on a captivating journey through time, exploring the mesmerizing evolution of fashion trends over the decades. Fashion has always been a reflection of society, capturing the spirit of each era and leaving an indelible mark on our collective memory. Join us as we delve into the world of iconic fashion trends, showcasing one prominent style per decade that continues to inspire and captivate us
Exquisite luxury brands at SDH. From fashion houses like Dolce & Gabbana, Gucci and Moschino to trendy labels like Off-White, MCM, and Versace, we offer a curated collection Women's Clothing of designer fashion.
Fusionthrift.com- A dive into the world of clothing and fashion.VanshArora88
In the ever-evolving realm of fashion and clothing, staying on trend is not just a choice; it’s a statement. Let’s embark on a journey through the dynamic landscape of style, where the only constant is change.
Migration Profile of Odisha with focus on BhubaneswarKamlesh Kumar
Migration is one the most important demographic component to determine the size, growth and structure of population of a particular region, besides fertility and mortality. For a large country like India, the study of movement of population in different parts of the country helps in understanding the dynamics of the society and societal change better. Bhubaneswar is one of the magnets for migrants in east India attributing to its exponential growth rates. This is an attempt to map the migration pattern in the city and the state.
Population Projection of Khordha District, ODISHA 2021-51Kamlesh Kumar
Work is based on Walter Isard's methods in a simplistic manner.
1. ARITHMATICAL INCREASE METHOD OF PROJECTION
2. GEOMETRIC INCREASE METHOD
3. INCREMENTAL INCREASE METHOD
DEMOGRAPHIC PROFILE OF CONTINENTAL ODISHAKamlesh Kumar
Although the state is endowed with vast natural resources it has remained on the bottom of the developmental chart of the nation. With such a reserve of natural resources and human resource potential, it is like a hibernating beast which must awake for good. Stealing the limelight of the most favourable smart city, the capital is growing like never before along with a few more cities. Yet the state remains mostly rural and lagging in most aspects except for the coastal regions. My analysis is that the state has not been given its due attention in planning which is the reason for its present backwardness.
COMMUNAL HARMONY: PUNJABI & TIBETANS IN DELHIKamlesh Kumar
LANDSCAPE AS TEXT
Delhi, the majestic, cosmopolitan, sprawling capital of the nation viewed as one of the global nodes bustling with life in haste. It has maintained its identity as a pluralistic amalgamation with myriads of ethno-religious groups and minority communities. Such is the very famous, our own ‘little Tibet’- Majnu Ka Tila situated at a stone’s throw from the Delhi University North Campus. Officially known as Aruna Nagar Colony is the universal gathering place
for Tibetans living around Delhi and a transit point for the people of the trans-Himalayan range and conversely a gateway to Tibet for the Indians and foreign tourists alike as the capital city enjoys a status of a flourishing educational and political hub.
Tall buildings on either side make the narrow alley so dark it’s as if the sun never makes it here. Shops on either side sell only exotic Tibetan jewellery, Buddhist artefacts and crockery. In this labyrinth of a colony, the stalls are full of copies of branded shoes and clothes, reflecting the latest in fashion trends across Asia. Many of the tiny outlets sell Buddhist curios and Tibetan literature. Ahead, the alley opens into a bright courtyard facing the monastery. Old ladies sit in the sun, making fresh momos and laphing, pancakes rolled with chilli paste. Besides MKT is a Foodie's paradise, the eateries here are not only popular for its momos, but one can also enjoy authentic Tibetan, Chinese and Korean delicacies along with the yummiest of the English pastries.
Majnu Ka Tila not only is limited to Tibetan community but constituted by the Punjabi community as well which has a historical context.
The area provides a microcosm of diversified India where there is invisible transition and diffusion of identity, culture of distinct communities and Indianisation of Tibetan lifestyle.
For instance, many Tibetans who cannot afford the rising rents of the Tibetan enclave (due to hotels and tourist activities) are forced to live in the Punjabi Basti where renting an apartment is cheaper comparatively. Living in Punjabi zone is seen influencing a cultural and identity loss. To diffuse with the Punjabi population is perceived as a risk “of identity loss”, and forgetting your Tibetan culture. These frontiers are mental, social and religious. Nonetheless, the ethnic groups interacting and sharing a space is a matter of pride as community harmony.
An overlay operation is much more than a simple merging of linework; all the attributes of the features taking part in the overlay are carried through. In general, there are two methods for performing overlay analysis—feature overlay (overlaying points, lines, or polygons) and raster overlay. Some types of overlay analysis lend themselves to one or the other of these methods. Overlay analysis to find locations meeting certain criteria is often best done using raster overlay (although you can do it with feature data). Of course, this also depends on whether your data is already stored as features or raster. It may be worthwhile to convert the data from one format to the other to perform the analysis.
Weighted Overlay
Overlays several raster files using a common measurement scale and weights each according to its importance.
The weighted overlay table allows the calculation of a multiple criteria analysis between several raster files.
Raster- The raster of the criteria being weighted.
Influence- The influence of the raster compared to the other criteria as a percentage of 100.
Field- The field of the criteria raster to use for weighting.
Remap- The scaled weights for the criterion.
In addition to numerical values for the scaled weights in Remap, the following options are available:
Restricted- Assigns the restricted value (the minimum value of the evaluation scale set, minus one) to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
No data - Assigns No Data to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
In the context of remote sensing, change detection refers to the process of identifying differences in the state of land features by observing them at different times. This process can be accomplished either manually (i.e., by hand) or with the aid of remote sensing software. Manual interpretation of change from satellite images or aerial photos involves an observer or analyst defining areas of interest and comparing them between images from two dates. This may be accomplished either on-screen (such as in a GIS) or on paper. When analyzing aerial photographs, a stereoscope which allows for two spatially-overlapping photos to be displayed in 3D, can aid photo interpretation. Manual image interpretation works well when assessing change between discrete classes (forest openings, land use and land cover maps) or when changes are large (e.g., heavy mechanized maneuver damage, engineering training impacts). Manual image interpretation is also an option when trying to determine change using images or photos from different sources (comparing historic aerial photographs to current satellite imagery).
Automated methods of remote sensing change detection usually are of two forms: post-classification change detection and image differencing using band ratios. In post-classification change detection, the images from each time period are classified using the same classification scheme into a number of discrete categories like land cover types. The two (or more) classifications are compared and the area that is classified the same or different is tallied. With image differencing, a band ratio such as NDVI is constructed from each input image, and the difference is taken between the band ratios of different times. In the case of differencing NDVI images, positive output values may indicate an increase in vegetation, negative values a decrease in vegetation, and values near zero no change. With either post-classification or image differencing change detection, it is necessary to specify a threshold below which differences between the two images is considered to be non-significant. The specification of thresholds is critical to the results of change detection analysis and usually must be found through an iterative process.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Accuracy assessment is an important part of any classification project. It compares the classified image to another data source that is considered to be accurate or ground truth data. Ground truth can be collected in the field; however, this is time consuming and expensive. Ground truth data can also be derived from interpreting high-resolution imagery, existing classified imagery, or GIS data layers.
The most common way to assess the accuracy of a classified map is to create a set of random points from the ground truth data and compare that to the classified data in a confusion matrix. Although this is a two-step process, you may need to compare the results of different classification methods or training sites, or you may not have ground truth data and are relying on the same imagery that you used to create the classification. To accommodate these other workflows, this process uses three geoprocessing tools: Create Accuracy Assessment Points, Update Accuracy Assessment Points, and Compute Confusion Matrix.
Thresholding
Thresholding is the process of identifying the pixels in a classified image that are the most likely to be classified incorrectly. These pixels are put into another class (usually class 0). These pixels are identified statistically, based upon the distance measures
that were used in the classification decision rule.
Accuracy Assessment : Error Matrix
Accuracy assessment is a general term for comparing the classification to geographical data that are assumed
to be true, in order to determine the accuracy of the classification process. Usually, the assumed-true data are derived from ground truth data. It is usually not practical to ground truth or otherwise test every pixel of a classified image. Therefore, a set of reference pixels is usually used. Reference pixels are points on the classified image for which actual data are (or will be) known. The reference pixels are randomly selected.
Overall accuracy: Overall accuracy is used to indicate the accuracy of whole classification (i.e. number of correctly classifier pixels divided by the total number of pixels in the error matrix)
User’s accuracy(commission error): User’s accuracy is regarded as the probability that a pixel classified on map actually represents that
class on the ground or reference data
Producer’s accuracy(omission error): Producer’s accuracy represents the probability of reference pixel being correctly classified
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
The objective of image classification is to classify each pixel into only one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). The classification techniques may be categorized either on the basis of training process (supervised and unsupervised) or on the basis of theoretical model (parametric and non-parametric).
Unsupervised classification is where the groupings of pixels with common characteristics are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and groups them into classes. The user can specify which algorism the software will use and the desired number of output classes but otherwise does not aid in the classification process. However, the user must have knowledge of the area being classified when the groupings of pixels with common characteristics produced by the computer have to be related to actual features on the ground (such as waterbodies, developed areas, forests, etc.).
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image. Input classes are selected based on the knowledge of the user. The user also sets the bounds for how similar other pixels must be to group them together. These bounds are often set based on the spectral characteristics of the input classes (AOI), plus or minus a certain increment (often based on “brightness” or strength of reflection in specific spectral bands). The user also designates the number of classes that the image is classified into.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Interpolation is the process of using points with known values to estimate values at other unknown points. It can be used to predict unknown values for any geographic point data, such as elevation, rainfall, noise levels, atmospheric components and so on.
The Inverse Distance Weighting (IDW) assumes each input point to have a local influence that diminishes with distance. It assumes that closer things are more alike than those that are farther apart. It weights the points closer to the processing cell greater than those further away. A specified number of points, or all points within a specified radius can be used to determine the output value of each location. To predict a value for any unmeasured location, IDW will use the measured values surrounding the prediction location. Those measured values closest to the prediction location will have more influence on the predicted value than those farther away.
Spline estimates values using a mathematical function that minimizes overall surface curvature, resulting in a smooth surface that passes exactly through the input points. This method is best for gently varying surfaces, such as elevation, water table heights, or pollution concentrations. A Regularized method creates a smooth, gradually changing surface with values that may lie outside the sample data range.
Kriging is a geostatistical interpolation technique that considers both the distance and the degree of variation between known data points when estimating values in unknown areas. Kriging assumes that the distance or direction between sample points reflects a spatial correlation that can be used to explain variation in the surface. The Kriging tool fits a mathematical function to a specified number of points, or all points within a specified radius, to determine the output value for each location. Kriging is a multistep process; it includes exploratory statistical analysis of the data, variogram modeling, creating the surface, and (optionally) exploring a variance surface. Kriging is most appropriate when you know there is a spatially correlated distance or directional bias in the data. It is often used in soil science and geology.
Trend is a statistical method that finds the surface that fits the sample points using a least-square regression fit. It fits one polynomial equation to the entire surface. This results in a surface that minimizes surface variance in relation to the input values. The surface is constructed so that for every input point, the total of the differences between the actual values and the estimated values (i.e., the variance) will be as small as possible.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
With increasing use of remote sensing, the need for crispier, accurate and enhanced precision has deemed to the improvement in the spectral and spatial resolution of remotely sensed imagery. For most of the systems, panchromatic images typically have higher resolution, while multispectral images offer information in several spectral channels. Resolution merge (also called pan-sharpening) allows us to combine advantages of both kinds of images by merging them into one.
The resolution merge or pan sharpening is the technique used to obtain high resolution multi-spectral images. The color information is collected from the coarse resolution satellite data and the intensity from the high resolution satellite data.
The main constraint is to preserve the spectral information for aspects like land use. Saving theimage from distortion of the spectral characteristics is important in the merged dataset.
The most common techniques for spatial enhancement of low-resolution imagery combining high and low resolution data can be used are: Intensity-Hue-Saturation, Principal Component, Multiplicative and Brovey Transform.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Remote Sensing: Normalized Difference Vegetation Index (NDVI)Kamlesh Kumar
The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses the visible and near-infrared (NIR) bands of the electromagnetic spectrum to analyze whether the target (image) being observed contains green vegetation or not. Healthy vegetation (chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. But it absorbs more red and blue light. This is why our eyes see vegetation as the colour green. If we could see near-infrared, then it would be strong for vegetation too.
It is basically measured through the use of Intensity, Hue and saturation of an image and through pixels as well.
The density of vegetation (NDVI) at a certain point on the image is equal to the difference in the intensities of reflected light in the red and infrared range divided by the sum of these intensities.
푁퐷푉퐼=((푁퐼푅−푅퐸퐷))/((푁퐼푅+푅퐸퐷))
The result of this formula generates a value between -1 and +1. If you have low reflectance (low values) in the red band and high reflectance in the NIR, this will yield a high NDVI value. And vice versa.
Remote Sensing: Principal Component AnalysisKamlesh Kumar
Principal components analysis is a orthogonal transformational technique (preserving the symmetry between vectors and angles) to reveal new set of data arguably better from the original data set and better capture the essential information as well. It happens often that some variables are highly correlated with a lot of duplication. Instead of discarding the redundant data, principal components analysis condenses the info. in inter-correlated variables into a few variables, called principal components.
The main idea of Principal Component Analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, while retaining the variation present in the dataset, up to the maximum extent.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
The advantage of digital imagery is that it allows us to manipulate the digital pixel values in the image. Even after the radiometric corrections image may still not be optimized for visual interpretation. An image 'enhancement' is basically anything that makes it easier or better to visually interpret. An enhancement is performed for a specific application as well. This enhancement may be inappropriate for another purpose, which would demand a different type of enhancement.
Filtering is used to enhance the appearance of an image. Spatial filters are designed to highlight or suppress specific features in an image based on their spatial frequency. ‘Rough’ textured areas of an image, where the changes in tone are abrupt, have high spatial frequencies, while ‘smooth’ areas with little variation have low spatial frequencies. A common filtering procedure involves moving a ‘matrix' of a few pixels in dimension (ie. 3x3, 5x5, etc.) over each pixel in the image, using mathematical calculation and replacing the central pixel with the new value.
A low-pass filter is designed to emphasize larger, homogeneous areas of similar tone and reduce the smaller detail in an image. Thus, low-pass filters generally serve to smooth the appearance of an image. In some cases, like 'low-pass filtering', the enhanced image can actually look worse than the original, but such an enhancement was likely performed to help the interpreter see low spatial frequency features among the usual high frequency clutter found in an image. High-pass filters do the opposite and serve to sharpen the appearance of fine detail in an image. Directional, or edge detection filters are designed to highlight linear features, such as roads or field boundaries. These filters can also be designed to enhance features which are oriented in specific directions.
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Mountainous regions occupy one-fourth of the world’s terrestrial surface, most rich in diverse landscapes and hold on to the biodiversity and cultural diversity along with supporting 10% of humankind with their direct life support base. Most mountainous regions have been at the far periphery of mainstream societal concerns for a long time. Remote, relatively inaccessible, they were generally pictured as difficulty, unyielding and unprofitable environments. Very less have focused attention on mountainous people and cultures, primitive religion, marginal survival, unusual adaptation to very high altitude, fraternal polyandry to obliterate informed communication and more meaningful analysis in practical sense. Early research concentrated mainly on specialised studies with little cross disciplinary endeavour. During the last few decades there have been spasmodic accounts of the highland and lowland mainly induced by events of great economic or political significance and due to the degradation of highlands which are potential threats to subjacent lowland population centre. Recent developments, expanding highland research and awareness spread by institutions and governments have shone a new ray of light towards the bright future. However, increased awareness with political advocacy must be pursued further.
Water is hydrosphere is made up of all the water on Earth. This includes all of the rivers, lakes, streams, oceans, groundwater, polar ice caps, glaciers and moisture in the air (like rain and snow). The hydrosphere is found on the surface of Earth, but also extends down several miles below, as well as several miles up into the atmosphere. So, there is a need for study of water as a scarce resource.
WHAT IS HYDROLOGICAL CYCLE
SYSTEM APPROACH IN HYDROLOGY
HYDROLOGIC INPUT & OUTPUT
VARIATION IN HYDROLOGICAL CYCLE
COMPONENTS
EVAPORATION
EVAPOTRANSPIRATION
PRECIPITATION
INTERCEPTION
INFILTRATION
GROUND WATER
RUN-OFF
HUMAN IMPACT
EARTH SURFACE
CLIMATE CHANGE
ATMOSPHERIC POLLUTION
MULTI PURPOSE PROJECTS
WATER WITHDRAWAL
MANAGEMENT AND CONTROL
An assessment on the temperate ecosystem with the following sub headings:
Geological evolution: Location and Extent
Atmospheric changes
Hydrological Changes
Land Degradation
Biodiversity Loss
Challenges to Human Community
Geosystem Approach: El Nino Southern Oscillation EffectsKamlesh Kumar
Earth system as a whole is very complex and dynamic, for that matter we prepare models to represent the functioning linkages and processes for better understanding. However, the geo-systems can not be summed up in just one model. Hence, we use system analysis approach, if we see Earth as a giant system, there're many sub-systems for better comprehension representing only a particular component of the system.
Here, I've tried to cover the geo-system approach siting a globe affecting example of the El Nino Southern Oscillation (ENSO) phenomena.
This report is detailed study of the research conducted in Kirori Mal College. The basic objective of this report is to get a tough insight in the use of research techniques. Geography, being a field science, a geographical enquiry always need to been supplemented through well planned Research. Research is an essential component of geographic enquire. It is a basic procedure to understand the earth as a home of humankind. Disaster management is an inseparable part of the discipline especially which deals with the study of natural phenomena. This research focuses upon the FIRE safety plan of the institution. It is carried out through observation, sketching, measurement, interviews, etc. The Research facilitate the collection of local level information that is not available through secondary sources.
In this report, various methodologies have been employed such as my, measurement and interviewing, photographing, examining, the collection and gathering of information at different corners of the institution and later, tabulating and computing them is an important part of the field work.
Furthermore, the research report has been prepared in concise form alongside with maps and diagrams for giving visual impressions. Moreover, it contains all the details of the procedures followed, methods, tools and techniques employed.
Disaster Prevention & Preparedness: Earthquake in NepalKamlesh Kumar
This report is detailed study of the field survey conducted in Kathmandu and Sindhupalchowk in Nepal on the earthquake disaster. The basic objective of this report is to get a tough insight in the use of field techniques regarding disaster management. Geography deals with human interaction with nature. This phenomenon can be better understood through field studies. Geography, being a field science, a geographical enquiry always need to be supplemented through well planned field surveys. Field is an essential component of geographic enquire. It is a basic procedure to understand the earth as a home of humankind. It is carried out through observation, sketching, measurement, interviews, etc. Field work takes the children out of the class and enables them to better understand the subject by visiting the areas practically giving an insight into the social, cultural and economic lives of the people. This also adds up the advantage of visiting the grass root levels of the society and ameliorative comprehension of the GLOCAL lives. It also has instilled various research making techniques in the budding geographers and shaping their thinking perspectives. The field surveys facilitate the collection of local level information that is not available through secondary sources.
In this report, various methodologies have been employed such as mapping, digitization, measurement and interviewing (questionnaires designing), the collection and gathering of information at the local level by conducting primary surveys and later, tabulating and computing them is an important part of the field survey.
Furthermore, the field study report has been prepared in concise form alongside with maps and diagrams for giving visual impressions. Moreover, it contains all the details of the procedures followed, methods, tools and techniques employed and the modern technology of navigation, satellite connections, GIS software have been very helpful in the pre-field drills.
The report has the following headings and sub-headings:
Introduction
Study area
Transit: Table & Maps
Disaster scenario of Nepal
Earthquake: Timeline
Causes
Impact
Who is helping Nepal?
Reconstruction and Rehabilitation Status
Objectives & Methodology
Literature review
Data representation and Analysis
Findings and Suggestions
Conclusions
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
1. 1
FASHION
‘Fashion’ is a notoriously difficult term to pin down, and it is extremely doubtful whether it is
possible to come up with necessary and sufficient conditions for something justifiably to be
called ‘fashionable’. Generally speaking, we can distinguish between two main categories in
our notion of fashion: one that fashion refers to clothing or that fashion is a general
mechanism, logic or ideology that, among other things, applies to the area of clothing.
Adam Smith1
, who was among the first philosophers to give fashion a central role in his
anthropology, claims that fashion applies first and foremost to areas in which taste is
a central concept. This applies in particular to clothes and furniture, but also to music, poetry
and architecture. Immanuel Kant provides a description of fashion that focuses on general
changes in human lifestyles: ‘All fashions are, by their very concept, mutable ways of living.’
Kant is perhaps the first fashion theorist to emphasize the new as an essential characteristic of
fashion. While earlier theorists had linked fashion to beauty, Kant emphasizes that it does not
have to have anything to do with beauty at all but it ‘degenerates into something fantastic and
even detestable’, since it is more a question of competition than a matter of taste. The new
has become self-justifying, it does not in principle need any particular qualities apart from
being new. There is in fashion a vital trait of modernity: the abolition of traditions. Nietzsche
emphasizes fashion as a characteristic of the modern because it is an indication of
emancipation from, among other things, authorities.
Clothes are inherently geographical objects, yet few of us consider the social and
economic significance of their journey from design to production to consumption. It is
proposed that fashion operates within and in relation to socio-economic life and the built
environment. This “cultural economy approach underscores the impossibility of severing
commercial or financial explanations of fashion from those that emphasize the aesthetic and
creative determinants of worth and value.”2
1
Fashion: A Philosophy, Lars Svendsen, Reaktion Books 2006
2
Geographies of fashion: Louise Crewe, Bloomsbury 2017
2. 2
EVOLUTION
The origin of fashion is usually linked to the emergence of mercantile capitalism in the late
medieval period. Europe was then experiencing considerable economic development leading
to swift cultural changes. It was here that changes in people’s clothing first acquired a
particular logic: change was no longer rare or random, but was rather cultivated for its own
sake. Clothes changed their basic shapes rapidly, with changes in superficial details taking
place even faster. Though fashion has been there even before that for example, in ancient
Egypt only the upper classes were allowed to wear sandals, and both the Greeks and the
Romans had rules regarding who was allowed to wear what. In the Middle Ages, however,
such rules were considerably more specific and comprehensive. Mercantile capitalism
had created a more ‘fluid’ society with social mobility, with laws also being introduced to
maintain class differences. Lavish clothing was a clear indication of vanity, something that
was a serious sin in itself. The sumptuary laws were constantly being broken as if the ban
made the commodities even more attractive. These laws served precisely to strengthen the
role of clothes as an important social marker as they created relatively clear criteria for the
social status of various objects. In the nineteenth century ‘democratization’ of fashion as
mass production as well as consumption mushroomed. At the start of the 20th century, the
fashion industry had global trade links, but it was yet to become globalized due to its
complex history and the power balances between the west and the east, with corporations that
were truly international, and fully-fledged fashion systems in multiple countries across the
world. This is not to say that fashion did not exist outside the West; style changes emerged on
other regions, moulded by local tastes and social structures. However, lab tested fashions
generated by designers, manufacturers, and promoted by retailers and media were to evolve
in the second half. The early 21st century saw a steady dissemination of trends via the
Internet, and financial and industrial growth in countries such as India and China. The rise of
the middle and upper classes in India, dictating potential domestic market, as is the case in
other countries that have invested in fashion, including China.
INDIA
The British introduced fashion in India adopting an extravagant lifestyle that could be
cultured as well as being indulgent in the ways, prior to that it was just limited to the
administrators. However, India’s tryst with industrialization quickened the pace of an
intrinsically agriculture-based nation. From the late 1950s, with Prime Minster Nehru
creating a clear mandate for moving the economy towards industry and agriculture as twin
3. 3
routes to progress, the nation was on the move upward. The surging middle class, seeking its
place in the emerging nation, had little time now to make its own clothes, and the office
worker preferred to have his or her clothes made by someone who specialized in the craft.
Men, particularly, preferred to patronize the local tailor, rather than trust the cutting of pants
and shirts to their womenfolk. The women, however, still took pride in the fact that their
cholis and their children’s garments were still hand stitched at home. India today, together
with China and Russia, has become part of the so-called Golden Triangle, attracting Europe’s
biggest designer labels. Luxury brand companies have been encouraged to invest in India by
several factors: the growth in the younger “aspiring” population; increasing salaries; a strong
eco- nomic climate; and a growing brand awareness attributed to increasing international
travel. The arrival of the international brands has undoubtedly inspired and motivated local
Indian talent to sign up with these brands until they have acquired the necessary skills and
experience to apply their own taste of locale.
This ritual has fed the Indian designer market like no other. The market for women’s fashion
in India is probably the most lucrative in terms of variety and scope. However, popular
brands are not the only ones driving the growth of India’s fashion industry. The Bollywood
influence in Indian fashion The flourishing Hindi film industry in India has played a key role
in transforming the way Indians dress. To reinforce their image and to protect their market
and revenues, the international brands reinforce this with the help of film stars to engage the
consumer emotionally with the dangers of counterfeiting. The tradition of the Great Indian
Wedding has a growing impact on the fashion and luxury sector.
1940s3 reflected nationalistic ethos due to national movements. The hand-spun Khadi fabric
became a powerful symbolism of the Swadeshi movement as opposed to the British mill-
cloth while the six-yard sari with simple borders ruled. The foundation of the Indian cinema
in this decade revolutionized the fashion scene. From Raj Kapoor to Dilip Kumar, men were
inspired by the European fashion of their matinee idols. White kurtas were still widely worn
with dhotis. Actresses were seen wearing puff sleeves in blouses which became a rage. The
salwar-kameez with a dupatta made its mark. Women from royal families became a style icon
of this decade made simple silk chiffon saris and delicate jewels very popular.
In the post-World war and post-independent era, the ‘50s decade witnessed celluloid
actresses like Madhubala, Meena Kumari and Nargis’s sartorial style inspired many young
women. While Madhubala’s sensual look in deep-cut blouses with Capri pants in Howrah
Bridge (1958) and full-length Anarkali suit in Mughal-E-Azam gained widespread
popularity, Meena Kumari mesmerised her fans with her courtesan look bedecked with
jewels. Translucent saris teamed with brocade blouse with sweetheart neckline were the
eternal favourites. Men took style lessons from Dev Anand who had girls swooning over his
look. Dev Anand was a trendsetter with his puffed hair, check shirts, mufflers and jackets.
The 1960-70, the ear of heavy jewellery and embroidered sarees saw the hem of the kameez
go shorter and arrival of bright colours. Body-hugging silhouettes came in vogue like skin-
tight short kurtas. Shorter and fitted blouses, a hint of skin, scarves and bouffant hairstyles
were the key features of the 60s. While Sharmila Tagore embraced the swimsuit in ‘An
Evening In Paris’ (1967), the Mumtaz style sari became hot favourites.
Bandhgala or jacket as worn by Jawaharlal Nehru became a staple in formal wear. Checkered
shirts, polo and Turtle-necks and bell-bottom pants for men were key fashion takeaways.
The 1970s was aptly called the ‘Decade of Decadence’ with both men and women adopting
the hipster style. This period brought with it a sense of experimentation, with bright colours
from demure to bold, actresses set fashion goals in crop-tops, pant-suits, maxis, skirts, polka
3
https://www.voylla.com/blog/7-fashion-wonders-of-free-indias-7-decades/
4. 4
dresses and fishnet stockings. The era also saw Indira Gandhi becoming the first woman
Prime Minister of India who was also a style icon. From her neatly starched handloom and
khadi saris, the Iron Lady of India was known for her tasteful sartorial choices. Men adopted
the ‘Guru kurta’ (round-neck A-line kurta popularised by Rajesh Khanna), safari suits and
slim pants. By the end of the 70s, jeans emerged as daily wear for men. Amitabh Bachchan,
the angry young man of the 70s was a trendsetter with his leather jackets and flared trousers.
The advent of television in people’s homes in ‘80s gave new meanings to fashion.
Salwar/chudidar became national attire for women. Printed saris with matching blouses
became common. Shoulder pads, blingy ornaments, outrageous colours were the hallmarks of
this decade. The buzzword for men’s fashion was colourful T-shirts and denim jackets.
90’s fashion was ruled by Indipop divas like Alisha Chinai and Suneeta Rao who had
immense fan following owing to their desi cool image. Film inspired fashion continued to
play an important role. Baggy pants were common in men. While Shah Rukh Khan sported
branded body- hugging tees while Salman Khan’s vests became a national craze. Govinda in
mismatched loud wardrobe became a style icon of the masses.
The new millennium had several international brands setting shop in India. Both men and
women sported new styles and experimented with cuts and patterns. Fashion designers like
Manish Malhotra and Sabyasachi experimented with new and old fabrics. Women preferred
sari in its slinky and glamorous avatar with deep-cut cleavage-bearing blouses. Low-waist
jeans too became hugely popular along with ethnic kurtis. Men’s fashion was more about
distressed jeans and cargo shorts.
5. 5
Fashion Education
• From the 1920s, Santiniketan and Sriniketan brought teachers from all over the world
to train students in a variety of disciplines. Crafts and clothes were an intrinsic part of
the syllabus.
• In Tamil Nadu, Kalakshetra, started in 1936, gave the Bharat Natyam respectability,
and ingrained the intricacies of its costumes and jewellery into the social fabric of the
time. The Adayar border saris became the fashion statement of the ladies who lunch
and those who professed to be art conscious.
• National Institute of Fashion Technology (NIFT) established in 1986 under the
umbrella of the Ministry of Textiles. Though it was meant to educate and produce
professionals for the fashion world, it has been more successful in creating fashion
designers.
• National Institute of Design (NID), an autonomous national institution for research,
service, and training in industrial design and visual communication setup in 1961
provides a multidisciplinary approach to design education, training, and practice.
Today, it is internationally recognized for the quality of its programs, which have
introduced changes in kind, rather than merely in degree.
The popularity of NIFT and NID have given rise to other design institutes, such as the Pearl
Academy in Delhi, Shreemati Nathibai Damodar Thackresey University and the Sophia
Polytechnic in Mumbai.
DELHI
New Delhi, for all its sombre capital-city status, is one of the most status-conscious cities in
India. With their lavish lifestyle, competitive nature and social consciousness, Delhi’s big
spenders are given to outdoing each other through sheer displays of wealth. Connaught Place,
Ambience and DLF Saket Mall is an ideal location and setting to become a true High Street.
According to Nehru, “New Delhi is the visible symbol of English power, with all its
ostentation and extravagance.”4
Delhi has some advantages compared to other big Indian
cities: one is the relatively cheap cost of labour, cosmopolitan culture and secondly the fact
that it is the capital of the country. Here, money flows freely because the north has a different
kind of income and has a different kind of customer, because the city like a cocoon and hub
at the same time. It condenses backward and inward as a hub, attracting work force and
people into the city while feeding off other cities.
FASHION AS VISIBLE EXPRESSION OF SOCIAL IDENTITY
The most visible material item of the fashion symbol is the garment, which carries multiple
and various meanings. The dynamism of the garment symbol can carry open or closed codes
depending on culture, gender and social location. Cloths can carry many significant signs
according to their shape, colour, surface decoration, embroidery techniques etc. And each one
can be the expression of identity over ethnicity, religious beliefs, age, education and social
class. Through observation of clothing styles over these items, the assumptions could be
made about a person’s identity.
4
India by Design: Michael Boroian and Alix De Poix, Wiley 2010
6. 6
Fashion is a form of non-verbal communication. The dressed body communicates our
personal and social identities. It expresses our thoughts, feelings, and desires, as well as
group membership. It means that clothing and fashion carry some hidden codes and these
codes are can be the signs of something because visual elements which carry also some
communicative purposes are the codes of the clothing and fashion. The significant and
communicative expression over clothing in the context of social groups mostly is seen at
sports team’s fans. For example, if you wear a t-shirt which belongs to Kolkata Knight Riders
team, it means that you support a team Kolkata Knight Riders and wearing that tshirt makes
you a part of that team. And you feel a group belonging.
FASHION IN AND AROUND UNIVERSITY OF DELHI
Delhi University is India's most highly regarded educational institution which attracts the
brightest of minds every year. The university is also an eclectic cocktail of myriad cultures
and personas and the varied colleges of the university serve as a canvas on which the students
showcase their fashionable side! Various colleges in Delhi University also have Fashion
Societies which function like any other college society, in terms of going for competitions,
cash prices, practicing throughout the day etc. What makes all these fashion societies a thing
of interest is that most of their annual productions are dramatic, visual and cinematographic
representation of social issues through fashion.
When it comes to representation of one’s self, ideaologies or identity, people from Delhi
University, be it a professor, student or staff use fashion at its fullest. The consumerism is not
only towards high-end brands but also street shopping. The campus area is surrounded by
market areas such as Kamla Nagar, Majnu ka Tila, Janpath, Sarojini Nagar and Lajpat Nagar.
These market places provide global fashion products at nominal prices mostly because they
are export surplus.
7. 7
These markets have made trendy and “in” fashion accessible to
almost everybody. One can easily find clothes and accessories
trending globally being sold on the streets of these market for
Rs.100-200.
The University of Delhi since its very inception has represented
a clash between the oriental and oxidant. A number of its
constituent colleges were founded by the British to educate
Indian youth. One’s choice of clothes speaks a lot about the
demographic culture they belong to. Thus as a student of this
university, wearing an outfit which is a fusion of the oriental and
oxidant actually represents the legacy of clashes between the
academia of two great cultural civilizations.
Kurtas are staple ethnic garment that come in a variety of
shapes, sizes, and cuts; and can be styled in endless ways that
are both ethic and a fusion of the east and west. In fact, the Kurta
and jeans which is the unofficial uniform of DU, is a prototype
of Indo-western wear.
8. 8
TAKE ON ENVIRONMENT
People with smaller wardrobes are more environmentally responsible than those who just
can't be seen wearing the same thing again and again. Shopping for new clothes is obvious to
cause an environmental impact somewhere on the planet. Polyester is the world's favourite
fibre for fashion. Yet, micro-fibres from washing polyester clothing is being pumped out of
our washing machines and into our sewers. These tiny particles of plastic are adding to the
problem of our plastic seas. Textile dyeing is the second largest polluter of potable water
globally. Many textile dyes are toxic and are banned in many countries. Toxic textile dyes are
bio-accumulative5
. Switching to cotton is not the easy answer either. Cotton farming requires
plenty of water and pesticides. Retailers may seduce us with 'natural fibres' but natural fibres
have to be spun, knitted or woven, dyed, sewn and transported on a global scale. Handcrafted
products from luxury fashion brands may be grossly overrated as their manufacturing remains
largely contingent on ruthless massacre of wildlife.
CONCLUSION
For the Indians themselves, for whom value for money will remain engrained in the psyche,
jewellery will remain an investment buy, but the outward representation of status that it
confers will feed the business of the foreign brands. Bollywood will remain a key influence,
and adulation of its stars and what they wear will continue to have an impact on the Indian
consumer. Commentaries abound in the media and on a multiplicity of fashion websites
offering Bollywood-inspired clothes. Stakeholders are waking up to the business
opportunities these are presenting, and many designers are now joining with companies or
movie stars to cash in on the retail potential. Whether it is the versatile saree, the humble
salwar kameez, or the Indo-western fusion of wearing kurta with jeans, many Indian woman
have managed to adapt various trends in fashionable clothing without compromising on the
beauty of all things Indian. Nevertheless, the fashion industry in India is constantly
transforming and growing, irrespective of such trends.
Fashion had not ended, therefore, but it had altered, and it was, potentially, on the brink of
another major shift towards the East. While it is unlikely that the Western fashion industry,
which has evolved since the Renaissance, will be subsumed, it will have to adapt quickly to
respond effectively to the global challenge. One should know that fashion is dynamic, and
while some styles manage to become timeless classics, other trends only enjoy a brief hype
before they die down.
5
https://www.numptynerd.net/globalisation-fashion-victims.html
9. 9
The fast fashion industry is bolstered by a growing influencer culture, in which social media
celebrities collaborate with big fast fashion companies as “brand ambassadors” to somehow
seamlessly intertwine these brands into their everyday lives. These fast fashion brands
provide accessible garments, and with the help of online shopping, consumption is even
easier. As a result, clothing production has doubled between 2000-2014, and the number of
garments the average consumer purchases a year has increased by 60 per cent. People want
their clothing cheap and trendy, and they want it quick.
However, trends die quickly and with that comes waste. Clothing produced by fast fashion
brands are oftentimes made from cheap materials, like polyester and acrylic, and not built to
last: The average American throws away 80 pounds of clothing every year. We’ve been
conditioned to believe that buying a garment and wearing it once is justifiable. It’s not. Due
to the growing demand in the fast fashion industry, we see a vast overproduction of clothing;
for example, the Copenhagen Fashion Summit reports that fashion is responsible for 92
million tons of solid waste dumped in landfills each year. This cultural shift on how we
consume clothing is leaving a huge mark on the planet. Fashion has become much more than
representation and being covered.