Search results for: diffuse reflectance

Authors: Sandra Regina Cavalcante, Rodolfo A. G. Vilela

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Introduction: Work accidents and occupational diseases are a big problem for public health around the world and the main health problem of workers with high social and economic costs. Brazil has shown progress over the last years, with the development of the regulatory system to improve safety and quality of life in the workplace. However, the situation is far from acceptable, because the occurrences remain high and there is a great gap between legislation and reality, generated by the low level of voluntary compliance with the law. Brazilian laws provide procedural legal instruments for both, to compensate the damage caused to the worker's health and to prevent future injuries. In the Judiciary, the prevention idea is in the collective action, effected through Brazilian Class Actions. Inhibitory guardianships may impose both, improvements to the working environment, as well as determine the interruption of activity or a ban on the machine that put workers at risk. Both the Labor Prosecution and trade unions have to stand to promote this type of action, providing payment of compensation for collective moral damage. Objectives: To verify how class actions (known as ‘public civil actions’), regulated in Brazilian legal system to protect diffuse, collective and homogeneous rights, are being used to protect workers' health and safety. Methods: The author identified and evaluated decisions of Brazilian Superior Court of Labor involving collective actions and work accidents. The timeframe chosen was December 2015. The online jurisprudence database was consulted in page available for public consultation on the court website. The categorization of the data was made considering the result (court application was rejected or accepted), the request type, the amount of compensation and the author of the cause, besides knowing the reasoning used by the judges. Results: The High Court issued 21,948 decisions in December 2015, with 1448 judgments (6.6%) about work accidents and only 20 (0.09%) on collective action. After analyzing these 20 decisions, it was found that the judgments granted compensation for collective moral damage (85%) and/or obligation to make, that is, changes to improve prevention and safety (71%). The processes have been filed mainly by the Labor Prosecutor (83%), and also appeared lawsuits filed by unions (17%). The compensation for collective moral damage had average of 250,000 reais (about US$65,000), but it should be noted that there is a great range of values found, also are several situations repaired by this compensation. This is the last instance resource for this kind of lawsuit and all decisions were well founded and received partially the request made for working environment protection. Conclusions: When triggered, the labor court system provides the requested collective protection in class action. The values of convictions arbitrated in collective actions are significant and indicate that it creates social and economic repercussions, stimulating employers to improve the working environment conditions of their companies. It is necessary to intensify the use of collective actions, however, because they are more efficient for prevention than reparatory individual lawsuits, but it has been underutilized, mainly by Unions.

Keywords: Brazilian Class Action, collective action, work accident penalization, workplace accident prevention, workplace protection law

Procedia PDF Downloads 241

Authors: G. Kontochristopoulos, T. Spiliopoulos, V. Markantoni, E. Platsidaki, A. Kouris, E. Balamoti, C. Bokotas, G. Haidemenos

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Introduction: There is a high patient demand for periorbital rejuvenation since the facial area is often the first to show visible signs of aging. With advancing age, there are sometimes marked changes that occur in the skin, fat, muscle and bone of the periorbital region, resulting to wrinkles and skin laxity. These changes are among the easiest areas to correct using several minimally invasive techniques, which have become increasingly popular over the last decade. Lasers, radiofrequency, botulinum toxin, fat grafting and fillers are available treatments sometimes in combination to traditional blepharoplasty. This study attempts to show the benefits of a minimally invasive approach to periorbital wrinkles and skin laxity that combine microneedling and 10% trichloroacetic acid (TCA) peels. Method: Eleven female patients aged 34-72 enrolled in the study. They all gave informed consent after receiving detailed information regarding the treatment procedure. Exclusion criteria in the study were previous treatment for the same condition in the past six months, pregnancy, allergy or hypersensitivity to the components, infection, inflammation and photosensitivity on the affected region. All patients had diffuse periorbital wrinkles and mild to moderate upper or lower eyelid skin laxity. They were treated with Automatic Microneedle Therapy System-Handhold and topical application of 10% trichloroacetic acid solution to each periorbital area for five minutes. Needling at a 0,25 mm depth was performed in both latelar (x-y) directions. Subsequently, the peeling agent was applied to each periorbital area for five minutes. Patients were subjected to the above combination every two weeks for a series of four treatments. Subsequently they were followed up regularly every month for two months. The effect was photo-documented. A Physician's and a Patient's Global Assessment Scale was used to evaluate the efficacy of the treatment (0-25% indicated poor response, 25%-50% fair, 50%-75% good and 75%-100% excellent response). Safety was assessed by monitoring early and delayed adverse events. Results: At the end of the study, almost all patients demonstrated significant aesthetic improvement. Physicians assessed a fair and a good improvement in 9(81.8% of patients) and 2(18.1% of patients) participants respectively. Patients Global Assessment rated a fair and a good response in 6 (54.5%) and 5 (45.4%) participants respectively. The procedure was well tolerated and all patients were satisfied. Mild discomfort and transient erythema were quite common during or immediately after the procedure, however only temporary. During the monthly follow up, no complications or scars were observed. Conclusions: Microneedling is known as a simple, office–based collagen induction therapy. Low concentration TCA solution applied to the epidermis that has been more permeable by microneedling, can reach the dermis more effectively. In the present study, chemical peels with 10% TCA acted as an adjuvant to microneedling, as it causes controlled skin damage, promoting regeneration and rejuvenation of tissues. This combined therapy improved periorbital fine lines, wrinkles, and overall appearance of the skin. Thus it constitutes an alternative treatment of periorbital skin aging, with encouraging results and minor side-effects.

Keywords: chemical peels, microneedling, periorbital wrinkles, skin laxity

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

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Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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Authors: Chuyuan Wang, Nayan Khare, Lily Villa, Patricia Solis, Elizabeth A. Wentz

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Maricopa County, Arizona, has a semi-arid hot desert climate that is one of the hottest regions in the United States. The exacerbated urban heat island (UHI) effect caused by rapid urbanization has made the urban area even hotter than the rural surroundings. The Phoenix metropolitan area experiences extremely high temperatures in the summer from June to September that can reach the daily highest of 120 °F (48.9 °C). Morbidity and mortality due to the environmental heat is, therefore, a significant public health issue in Maricopa County, especially because it is largely preventable. Public records from the Maricopa County Department of Public Health (MCDPH) revealed that between 2012 and 2016, there were 10,825 incidents of heat-related morbidity incidents, 267 outdoor environmental heat deaths, and 173 indoor heat-related deaths. A lot of research has examined heat-related death and its contributing factors around the world, but little has been done regarding heat-related morbidity issues, especially for regions that are naturally hot in the summer. The objective of this study is to examine the demographic, socio-economic, housing, and environmental factors that contribute to heat-related morbidity in Maricopa County. We obtained heat-related morbidity data between 2012 and 2016 at census tract level from MCDPH. Demographic, socio-economic, and housing variables were derived using 2012-2016 American Community Survey 5-year estimate from the U.S. Census. Remotely sensed Landsat 7 ETM+ and Landsat 8 OLI satellite images and Level-1 products were acquired for all the summer months (June to September) from 2012 and 2016. The National Land Cover Database (NLCD) 2016 percent tree canopy and percent developed imperviousness data were obtained from the U.S. Geological Survey (USGS). We used ordinary least squares (OLS) regression analysis to examine the empirical relationship between all the independent variables and heat-related morbidity rate. Results showed that higher morbidity rates are found in census tracts with higher values in population aged 65 and older, population under poverty, disability, no vehicle ownership, white non-Hispanic, population with less than high school degree, land surface temperature, and surface reflectance, but lower values in normalized difference vegetation index (NDVI) and housing occupancy. The regression model can be used to explain up to 59.4% of total variation of heat-related morbidity in Maricopa County. The multiscale geographically weighted regression (MGWR) technique was then used to examine the spatially varying relationships between heat-related morbidity rate and all the significant independent variables. The R-squared value of the MGWR model increased to 0.691, that shows a significant improvement in goodness-of-fit than the global OLS model, which means that spatial heterogeneity of some independent variables is another important factor that influences the relationship with heat-related morbidity in Maricopa County. Among these variables, population aged 65 and older, the Hispanic population, disability, vehicle ownership, and housing occupancy have much stronger local effects than other variables.

Keywords: census, empirical modeling, heat-related morbidity, spatial analysis

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Authors: André Python

Abstract:

To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Patricia Shirley Almeida Prado, Liz Brito, Selma Paixão Argollo, Gracie Moreira, Leticia Matos Sobrinho

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Diffuse idiopathic skeletal hyperostosis (DISH) is a degenerative bone disease also known as Forestier´s disease and ankylosing hyperostosis of the spine is characterized by a tendency toward ossification of half the anterior longitudinal spinal ligament without intervertebral disc disease. DISH is not considered to be osteoarthritis, although the two conditions commonly occur together. Diagnostic criteria include fusion of at least four vertebrae by bony bridges arising from the anterolateral aspect of the vertebral bodies. These vertebral bodies have a 'dripping candle wax' appearance, also can be seen periosteal new bone formation on the anterior surface of the vertebral bodies and there is no ankylosis at zygoapophyseal facet joint. Clinically, patients with DISH tend to be asymptomatic some patients mention moderate pain and stiffness in upper back. This disease is more common in man, uncommon in patients younger than 50 years and rare in patients under 40 years old. In modern populations, DISH is found in association with obesity, (type II) diabetes; abnormal vitamin A metabolism and also associated with higher levels of serum uric acid. There is also some association between the increase of risk of stroke or other cerebrovascular disease. The DISH condition can be confused with Heterotopic Ossification, what is the bone formation in the soft tissues as the result of trauma, wounding, surgery, burnings, prolonged immobility and some central nervous system disorder. All these conditions have been described extensively as myositis ossificans which can be confused with the fibrodysplasia (myositis) ossificans progressive. As in the DISH symptomatology it can be asymptomatic or extensive enough to impair joint function. A third confusion osteoarthritis disease that can bring confusion are the enthesopathies that occur in the entire skeleton being common on the ischial tuberosities, iliac crests, patellae, and calcaneus. Ankylosis of the sacroiliac joint by bony bridges may also be found. CASE 1: this case is skeletal remains presenting skull, some vertebrae and scapulae. This case remains unidentified and due to lack of bone remains. Sex, age and ancestry profile was compromised, however the DISH pathognomonic findings and diagnostic helps to estimate sex and age characteristics. Moreover to presenting DISH these skeletal remains also showed some bone alterations and non-metrics as fusion of the first vertebrae with occipital bone, maxillae and palatine torus and scapular foramen on the right scapulae. CASE 2: this skeleton remains shows an extensive bone heterotopic ossification on the great trochanter area of left femur, right fibula showed a healed fracture in its body however in its inteosseous crest there is an extensive bone growth, also in the Ilium at the region of inferior gluteal line can be observed some pronounced bone growth and the skull presented a pronounced mandibular, maxillary and palatine torus. Despite all these pronounced heterotopic ossification the whole skeleton presents moderate bone overgrowth that is not linked with aging, since the skeleton belongs to a young unidentified individual. The appropriate osteopathological diagnosis support the human identification process through medical reports and also assist with epidemiological data that can strengthen vulnerable anthropological estimates.

Keywords: bone disease, DISH, human identification, human remains

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Svebor Secak

Abstract:

This four-year artistic research project hosted by the University of New England, Australia has set the goal to experiment with non-conventional ways of presenting a language-based narrative in dance using insights of recent theoretical writing on performance, addressing the research question: How to transform an archival recording of a neoclassical ballet performance into a new artistic dance video by implementing postmodern philosophical concepts? The Creative Practice component takes the form of a dance video Hamlet Revisited which is a reworking of the archival recording of the neoclassical ballet Hamlet, augmented by new material, produced using resources, technicians and dancers of the Croatian National Theatre in Zagreb. The methodology for the creation of Hamlet Revisited consisted of extensive field and desk research after which three dancers were shown the recording of original Hamlet and then created their artistic response to it based on their reception and appreciation of it. The dancers responded differently, based upon their diverse dancing backgrounds and life experiences. They began in the role of the audience observing video of the original ballet and transformed into the role of the choreographer-performer. Their newly recorded material was edited and juxtaposed with the archival recording of Hamlet and other relevant footage, allowing for postmodern features such as aleatoric content, synchronicity, eclecticism and serendipity, that way establishing communication on a receptive reader-response basis, thus blending the roles of the choreographer, performer and spectator, creating an original work of art whose significance lies in the relationship and communication between styles, old and new choreographic approaches, artists and audiences and the transformation of their traditional roles and relationships. In editing and collating, the following techniques were used with the intention to avoid the singular narrative: fragmentation, repetition, reverse-motion, multiplication of images, split screen, overlaying X-rays, image scratching, slow-motion, freeze-frame and simultaneity. Key postmodern concepts considered were: deconstruction, diffuse authorship, supplementation, simulacrum, self-reflexivity, questioning the role of the author, intertextuality and incredulity toward grand narratives - departing from the original story, thus personalising its ontological themes. From a broad brush of diverse concepts and techniques applied in an almost prescriptive manner, the project focuses on intertextuality that proves to be valid on at least two levels. The first is the possibility of a more objective analysis in combination with a semiotic structuralist approach moving from strict relationships between signs to a multiplication of signifiers, considering the dance text as an open construction, containing the elusive and enigmatic quality of art that leaves the interpretive position open. The second one is the creation of the new work where the author functions as the editor, aware and conscious of the interplay of disparate texts and their sources which co-act in the mind during the creative process. It is argued here that the eclectic combination of the old and new material through constant oscillations of different discourses upon the same topic resulted in a transmodern integrationist recent work of art that might be applied as a model for reconsidering existing choreographic creations.

Keywords: Ballet Hamlet, intertextuality, transformation, transmodern dance video

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Authors: Delsy Salinas, Andreia Garcês, Augusto Silva, Paula Brilhante Simões

Abstract:

Urinary tract infection (UTI) is a common disease affecting dogs and cats in both community and hospital environment. Bacteria is the most frequent agent isolated, fewer than 1% of infections are due to parasitic, fungal, or viral agents. Common symptoms and laboratory abnormalities includeabdominal pain, pyrexia, renomegaly, and neutrophilia with left shift. A rapid and precise identification of the bacterial agent is still a challenge in veterinarian laboratories. Therefore, this cross-sectional study aims to describe bacterial colony patterns of urine samples by using chromID™ CPS® EliteAgar (BioMérieux, France) from canine and feline specimens submitted to a veterinary laboratory in Portugal (INNO Veterinary Laboratory, Braga)from January to March2022. All urine samples were cultivated in CPS Elite Agar with calibrated 1 µL inoculating loop and incubated at 37ºC for 18-24h. Color,size, and shape (regular or irregular outline)were recorded for all samples. All colonies were classified as Gram-negative or Gram-positive bacteriausing Gram stain (PREVI® Color BioMérieux, France) and determined if they were pure colonies. Identification of bacteria species was performed using GP and GN cards inVitek 2® Compact(BioMérieux, France). A total of 256/1003 submitted urine samples presented bacterial growth, from which 172 isolates were included in this study. The sample’s population included 111 dogs (n=45 males and n=66 females) and 61 cats (n=35 males and n=26 females). The most frequent isolated bacteria wasEscherichia coli (44,7%), followed by Proteus mirabilis (13,4%). All Escherichia coli isolates presented red to burgundy colonies, a colony diameter between 2 to 6 mm, and regular or irregular outlines. Similarly, 100% of Proteus mirabilis isolates were dark yellow colonies with a diffuse pigment and the same size and shape as Escherichia coli. White and pink pale colonies where Staphylococcus species exclusively and S. pseudintermedius was the most frequent (8,2 %). Cian to blue colonies were mostly Enterococcusspp. (8,2%) and Streptococcus spp. (4,6%). Beige to brown colonies were Pseudomonas aeruginosa (2,9%) and Citrobacter spp. (1,2%).Klebsiella spp.,Serratia spp. and Enterobacter spp were green colonies. All Gram-positive isolates were 1 to 2 mm diameter long and had a regular outline, meanwhile, Gram-negative rods presented variable patterns. This results showed that theprevalence of E coli and P. mirabilis as uropathogenic agents follows the same trends in Europe as previously described in other studies. Both agents presented a particular color pattern in CPS Elite Agar to identify them without needing complementary tests. No other bacteria genus could be correlated strongly to a specific color pattern, and similar results have been observed instudies using human’s samples. Chromogenic media shows a great advantage for common urine bacteria isolation than traditional COS, McConkey, and CLEDAgar mediums in a routine context, especially when mixed fermentative Gram-negative agents grow simultaneously. In addition, CPS Elite Agar is versatile for Artificial Intelligent Reading Plates Systems. Routine veterinarian laboratories could use CPS Elite Agar for a rapid screening for bacteria identification,mainlyE coli and P.mirabilis, saving 6h to 10h of automatized identification.

Keywords: cats, CPS elite agar, dogs, urine pathogens

Procedia PDF Downloads 66

Authors: Joyjit Dey, Souvik Sen

Abstract:

Middle Permian Barakar formation is the major economic coal bearing unit of vast east-west trending Damodar Valley basin of Gondwana coalfield. Primary sedimentary structures were studied from the core holes, which represent majorly four facies groups: sandstone dominated facies, sandstone-shale heterolith facies, shale facies and coal facies. Total eight major coal seams have been identified with the bottom most seam being the thickest. Laterally, continuous coal seams were deposited in the calm and quiet environment of extensive floodplain swamps. Channel sinuosity and lateral channel migration/avulsion results in lateral facies heterogeneity and coal splitting. Geophysical well logs (Gamma-Resistivity-Density logs) have been used to establish the vertical and lateral correlation of various litho units field-wide, which reveals the predominance of repetitive fining upwards cycles. Well log data being a permanent record, offers a strong foundation for generating log based property evaluation and helps in characterization of depositional units in terms of lateral and vertical heterogeneity. Low gamma, high resistivity, low density is the typical coal seam signatures in geophysical logs. Here, we have used a density cutoff of 1.6 g/cc as a primary discriminator of coal and the same has been employed to compute various coal assay parameters, which are ash, fixed carbon, moisture, volatile content, cleat porosity, vitrinite reflectance (VRo%), which were calibrated with the laboratory based measurements. The study shows ash content and VRo% increase from west to east (towards basin margin), while fixed carbon, moisture and volatile content increase towards west, depicting increased coal quality westwards. Seam wise cleat porosity decreases from east to west, this would be an effect of overburden, as overburden pressure increases westward with the deepening of basin causing more sediment packet deposited on the western side of the study area. Coal is a porous, viscoelastic material in which velocity and strain both change nonlinearly with stress, especially for stress applied perpendicular to the bedding plane. Usually, the coal seam has a high velocity contrast relative to its neighboring layers. Despite extensive discussion of the maceral and chemical properties of coal, its elastic characteristics have received comparatively little attention. The measurement of the elastic constants of coal presents many difficulties: sample-to-sample inhomogeneity and fragility and velocity dependence on stress, orientation, humidity, and chemical content. In this study, a conclusive empirical equation VS= 0.80VP-0.86 has been used to model shear velocity from compression velocity. Also the same has been used to compute various geomechanical moduli. Geomech analyses yield a Poisson ratio of 0.348 against coals. Average bulk modulus value is 3.97 GPA, while average shear modulus and Young’s modulus values are coming out as 1.34 and 3.59 GPA respectively. These middle Permian Barakar coals show an average 23.84 MPA uniaxial compressive strength (UCS) with 4.97 MPA cohesive strength and 0.46 as friction coefficient. The output values of log based proximate parameters and geomechanical moduli suggest a medium volatile Bituminous grade for the studied coal seams, which is found in the laboratory based core study as well.

Keywords: core analysis, coal characterization, geophysical log, geo-mechanical moduli

Procedia PDF Downloads 191

Authors: Elhadi Nasr, Ibrahim Ramadan

Abstract:

Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

Procedia PDF Downloads 382