Search results for: satellite mapping

Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

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Authors: Daniel R. Zeh, Michelle R. Heupel, Mark Hamann, Rhondda Jones, Colin J. Limpus, Helene Marsh

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Marine mammals live in an environment with water temperatures nearly always lower than the mammalian core body temperature of 35 - 38°C. Marine mammals can lose heat at high rates and have evolved a range of adaptations to minimise heat loss. Our project tracked dugongs to examine if there was a discoverable relationship between the animals’ movements and the temperature of their environment that might suggest behavioural thermoregulation. Twenty-nine dugongs were fitted with acoustic and satellite/GPS transmitters in 2012, 2013 and 2014 in Moreton Bay Queensland at the high latitude limit of the species’ winter range in eastern Australia on 30 occasions (one animal was tagged twice). All 22 animals that stayed in the area and had functional transmitters made at least one (and up to 66) return trip(s) to the warmer oceanic waters outside the bay where seagrass is unavailable. Individual dugongs went in and out of the bay in synchrony with the tides and typically spent about 6 hours in the oceanic water. There was a diel pattern in the movements: 85% of outgoing trips occurred between midnight and noon. There were significant individual differences, but the likelihood of a dugong leaving the bay was independent of body length or sex. In Quarter 2 (April – June), the odds of a dugong making a trip increased by about 40% for each 1°C increase in the temperature difference between the bay and the warmer adjacent oceanic waters. In Quarter 3, the odds of making a trip were lower when the outside –inside bay temperature differences were small or negative but increased by a factor of up to 2.12 for each 1°C difference in outside – inside temperatures. In Quarter 4, the odds of making a trip were higher when it was cooler outside the bay and decreased by a factor of nearly 0.5 for each 1°C difference in outside – inside bay temperatures. The activity spaces of the dugongs generally declined as winter progressed suggesting a change in the cost-effectiveness of moving outside the bay. Our analysis suggests that dugongs can thermoregulate their core temperature through the behaviour of moving to water having more favourable temperature.

Keywords: acoustic, behavioral thermoregulation, dugongs, movements, satellite, telemetry, quick fix GPS

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Authors: Qiaowen Lin

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The 3D cadastre is an inevitable choice to meet the needs of real cadastral management. Nowadays, more attention is given to the technical aspects of 3D cadastre, resulting in the imbalance within this field. To fulfill this research gap, the stakeholder, which has been regarded as the determining factor in cadastral change has been studied. Delphi method, Michael rating, and stakeholder mapping are used to identify and classify the stakeholders in 3D cadastre. It is concluded that the project managers should pay more attention to the interesting appeal of the key stakeholders and different coping strategies should be adopted to facilitate the transition to 3D cadastre.

Keywords: stakeholders, three dimension, cadastre, transtion

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Authors: Tshilidzi C. Manyanya, Nthaduleni S. Nethengwe, Edmore Kori

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The UNFCCC, FAO, GCF, IPCC and other global structures advocate for agro-ecology do address food security and sovereignty. However, most of the expected outcomes concerning agro-ecological were not empirically tested for universal application. Agro-ecology is theorised to increase crop health over ago-ecological farms and decrease over conventional farms. Increased crop health means increased carbon sequestration and thus less CO2 in the atmosphere. This is in line with the view that global warming is anthropogenically enhanced through GHG emissions. Agro-ecology mainly affects crop health, soil carbon content and yield on the cultivated land. Economic sustainability is directly related to yield capacity, which is theorized to increase by 3-10% in a space of 3 - 10 years as a result of agro-ecological implementation. This study aimed to empirically assess the practicality and validity of these assumptions. The study utilized mainly GIS and RS techniques to assess the effectiveness of agro-ecology in crop health improvement from satellite images. The assessment involved a longitudinal study (2013 – 2015) assessing the changes that occur after a farm retrofits from conventional agriculture to agro-ecology. The assumptions guided the objectives of the study. For each objective, an agro-ecological farm was compared with a conventional farm in the same climatic conditional occupying the same general location. Crop health was assessed using satellite images analysed through ArcGIS and Erdas. This entailed the production of NDVI and Re-classified outputs of the farm area. The NDVI ranges of the entire period of study were thus compared in a stacked histogram for each farm to assess for trends. Yield capacity was calculated based on the production records acquired from the farmers and plotted in a stacked bar graph as percentages of a total for each farm. The results of the study showed decreasing crop health trends over 80% of the conventional farms and an increase over 80% of the organic farms. Yield capacity showed similar patterns to those of crop health. The study thus showed that agro-ecology is an effective strategy for crop-health improvement and yield increase.

Keywords: agro-ecosystem, conventional farm, dialectical, sustainability

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Authors: Giuseppina Anna Giorgio, Angela Lorusso, Maria Ragosta, Vito Telesca

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Climate change is a major public health threat due to the effects of extreme weather events on human health and on quality of life in general. In this context, mean temperatures are increasing, in particular, extreme temperatures, with heat waves becoming more frequent, more intense, and longer lasting. In many cities, extreme heat waves have drastically increased, giving rise to so-called Urban Heat Island (UHI) phenomenon. In an urban centre, maximum temperatures may be up to 10° C warmer, due to different local atmospheric conditions. UHI occurs in the metropolitan areas as function of the population size and density of a city. It consists of a significant difference in temperature compared to the rural/suburban areas. Increasing industrialization and urbanization have increased this phenomenon and it has recently also been detected in small cities. Weather conditions and land use are one of the key parameters in the formation of UHI. In particular surface urban heat island is directly related to temperatures, to land surface types and surface modifications. The present study concern a UHI analysis of Matera city (Italy) based on the analysis of temperature, change in land use and land cover, using Corine Land Cover maps and satellite Landsat images. Matera, located in Southern Italy, has a typical Mediterranean climate with mild winters and hot and humid summers. Moreover, Matera has been awarded the international title of the 2019 European Capital of Culture. Matera represents a significant example of vernacular architecture. The structure of the city is articulated by a vertical succession of dug layers sometimes excavated or partly excavated and partly built, according to the original shape and height of the calcarenitic slope. In this study, two meteorological stations were selected: MTA (MaTera Alsia, in industrial zone) and MTCP (MaTera Civil Protection, suburban area located in a green zone). In order to evaluate the increase in temperatures (in terms of UHI occurrences) over time, and evaluating the effect of land use on weather conditions, the climate variability of temperatures for both stations was explored. Results show that UHI phenomena is growing in Matera city, with an increase of maximum temperature values at a local scale. Subsequently, spatial analysis was conducted by Landsat satellite images. Four years was selected in the summer period (27/08/2000, 27/07/2006, 11/07/2012, 02/08/2017). In Particular, Landsat 7 ETM+ for 2000, 2006 and 2012 years; Landsat 8 OLI/TIRS for 2017. In order to estimate the LST, Mono Window Algorithm was applied. Therefore, the increase of LST values spatial scale trend has been verified, in according to results obtained at local scale. Finally, the analysis of land use maps over the years by the LST and/or the maximum temperatures measured, show that the development of industrialized area produces a corresponding increase in temperatures and consequently a growth in UHI.

Keywords: climate variability, land surface temperature, LANDSAT images, urban heat island

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Ali Mohammadi

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Whenever there is a need to dig the ground, the presence of a surveyor is required to control the map. In projects such as dams and tunnels, these controls are more important because any mistakes can increase the cost. Also, time is great importance in These projects have and one of the ways to reduce the drilling time is to use techniques that can reduce the mapping time in these projects. Nowadays, with the existence of mobile phones, we can design apps that perform calculations and drawing for us on the mobile phone. Also, if we have a device that requires a computer to access its information, by designing an app, we can transfer its information to the mobile phone and use it, so we will not need to go to the office.

Keywords: app, tunnel, excavation, dam

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Ozgu Hafizoglu

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An analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with physical, behavioral, principal relations that are essential to learning, discovery, and innovation. The Cognitive Model of Analogy (CMA) leads and creates patterns of pathways to transfer information within and between domains in science, just as happens in the brain. The connectome of the brain shows how the brain operates with mental leaps between domains and mental hops within domains and the way how analogical reasoning mechanism operates. This paper demonstrates the CMA as an evolutionary approach to science, technology, and life. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions in the new era, especially post-pandemic. In this paper, we will reveal how to draw an analogy to scientific research to discover new systems that reveal the fractal schema of analogical reasoning within and between the systems like within and between the brain regions. Distinct phases of the problem-solving processes are divided thusly: stimulus, encoding, mapping, inference, and response. Based on the brain research so far, the system is revealed to be relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain’s mechanism in macro context; brain and spinal cord, and micro context: glia and neurons, relative to matching conditions of analogical reasoning and relational information, encoding, mapping, inference and response processes, and verification of perceptual responses in four-term analogical reasoning. Finally, we will relate all these terminologies with these mental leaps, mental maps, mental hops, and mental loops to make the mental model of CMA clear.

Keywords: analogy, analogical reasoning, brain connectome, cognitive model, neurons and glia, mental leaps, mental hops, mental loops

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Authors: Fanous Mohammadi, Majid H. Tangestani, Mohammad H. Tayebi

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This research aims to evaluate and compare Geographical Information Systems (GIS)-based fuzzy models for producing orogenic gold prospectivity maps in the Saqqez area, NW of Iran. Gold occurrences are hosted in sericite schist and mafic to felsic meta-volcanic rocks in this area and are associated with hydrothermal alterations that extend over ductile to brittle shear zones. The predictor maps, which represent the Pre-(Source/Trigger/Pathway), syn-(deposition/physical/chemical traps) and post-mineralization (preservation/distribution of indicator minerals) subsystems for gold mineralization, were generated using empirical understandings of the specifications of known orogenic gold deposits and gold mineral systems and were then pre-processed and integrated to produce mineral prospectivity maps. Five fuzzy logic operators, including AND, OR, Fuzzy Algebraic Product (FAP), Fuzzy Algebraic Sum (FAS), and GAMMA, were applied to the predictor maps in order to find the most efficient prediction model. Prediction-Area (P-A) plots and field observations were used to assess and evaluate the accuracy of prediction models. Mineral prospectivity maps generated by AND, OR, FAP, and FAS operators were inaccurate and, therefore, unable to pinpoint the exact location of discovered gold occurrences. The GAMMA operator, on the other hand, produced acceptable results and identified potentially economic target sites. The P-A plot revealed that 68 percent of known orogenic gold deposits are found in high and very high potential regions. The GAMMA operator was shown to be useful in predicting and defining cost-effective target sites for orogenic gold deposits, as well as optimizing mineral deposit exploitation.

Keywords: mineral prospectivity mapping, fuzzy logic, GIS, orogenic gold deposit, Saqqez, Iran

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Authors: Sujata S. Kulkarni

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Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.

Keywords: compressed sensing, feature extraction, image classification, texture analysis

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Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

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Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

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Authors: Narjes Abbasabadi

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As the world continues to urbanize and suburbanize, where suburbanization associated with mass sprawl has been the dominant form of this expansion, sustainable development challenges will be more concerned. Sprawling, characterized by low density and automobile dependency, presents significant environmental issues regarding energy consumption and Co2 emissions. This paper examines the vertical expansion of suburbs integrated into mass transit nodes as a planning strategy for boosting density, intensification of land use, conversion of single family homes to multifamily dwellings or mixed use buildings and development of viable alternative transportation choices. It analyzes the spatial patterns of tall building transit-oriented development (TB-TOD) of suburban regions in Sydney (Australia), Toronto (Canada), and Washington D.C. (United States). The main objectives of this research seek to understand the effect of the new morphology of suburban tall, the physical dimensions of individual buildings and their arrangement at a larger scale with energy efficiency. This study aims to answer these questions: 1) why and how can the potential phenomenon of vertical expansion or high-rise development be integrated into suburb settings? 2) How can this phenomenon contribute to an overall denser development of suburbs? 3) Which spatial pattern or typologies/ sub-typologies of the TB-TOD model do have the greatest energy efficiency? It addresses these questions by focusing on 1) energy, heat energy demand (excluding cooling and lighting) related to design issues at two levels: macro, urban scale and micro, individual buildings—physical dimension, height, morphology, spatial pattern of tall buildings and their relationship with each other and transport infrastructure; 2) Examining TB-TOD to provide more evidence of how the model works regarding ridership. The findings of the research show that the TB-TOD model can be identified as the most appropriate spatial patterns of tall buildings in suburban settings. And among the TB-TOD typologies/ sub-typologies, compact tall building blocks can be the most energy efficient one. This model is associated with much lower energy demands in buildings at the neighborhood level as well as lower transport needs in an urban scale while detached suburban high rise or low rise suburban housing will have the lowest energy efficiency. The research methodology is based on quantitative study through applying the available literature and static data as well as mapping and visual documentations of urban regions such as Google Earth, Microsoft Bing Bird View and Streetview. It will examine each suburb within each city through the satellite imagery and explore the typologies/ sub-typologies which are morphologically distinct. The study quantifies heat energy efficiency of different spatial patterns through simulation via GIS software.

Keywords: energy efficiency, spatial pattern, suburb, tall building transit-oriented development (TB-TOD)

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Authors: Zermina Q., Wasif Y., Naeem S., Urooj S., Sajid R. A.

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Land degradation, a leading environemtnal problem and a decrease in the quality of land has become a major global issue, caused by human activities. By land degradation, more than half of the world’s drylands are affected. The worldwide scope of main saline soils is approximately 955 M ha, whereas inferior salinization affected approximately 77 M ha. In irrigated areas, a total of 58% of these soils is found. As most of the vegetation types requires fertile soil for their growth and quality production, salinity causes serious problem to the production of these vegetation types and agriculture demands. This research aims to identify the salt affected areas in the selected part of Indus Delta, Sindh province, Pakistan. This particular mangroves dominating coastal belt is important to the local community for their crop growth. Object based image analysis approach has been adopted on Landsat TM imagery of year 2011 by incorporating different mathematical band ratios, thermal radiance and salinity index. Accuracy assessment of developed salinity landcover map was performed using Erdas Imagine Accuracy Assessment Utility. Rain factor was also considered before acquiring satellite imagery and conducting field survey, as wet soil can greatly affect the condition of saline soil of the area. Dry season considered best for the remote sensing based observation and monitoring of the saline soil. These areas were trained with the ground truth data w.r.t pH and electric condutivity of the soil samples. The results were obtained from the object based image analysis of Keti bunder and Kharo chan shows most of the region under low saline soil.Total salt affected soil was measured to be 46,581.7 ha in Keti Bunder, which represents 57.81 % of the total area of 80,566.49 ha. High Saline Area was about 7,944.68 ha (9.86%). Medium Saline Area was about 17,937.26 ha (22.26 %) and low Saline Area was about 20,699.77 ha (25.69%). Where as total salt affected soil was measured to be 52,821.87 ha in Kharo Chann, which represents 55.87 % of the total area of 94,543.54 ha. High Saline Area was about 5,486.55 ha (5.80 %). Medium Saline Area was about 13,354.72 ha (14.13 %) and low Saline Area was about 33980.61 ha (35.94 %). These results show that the area is low to medium saline in nature. Accuracy of the soil salinity map was found to be 83 % with the Kappa co-efficient of 0.77. From this research, it was evident that this area as a whole falls under the category of low to medium saline area and being close to coastal area, mangrove forest can flourish. As Mangroves are salt tolerant plant so this area is consider heaven for mangrove plantation. It would ultimately benefit both the local community and the environment. Increase in mangrove forest control the problem of soil salinity and prevent sea water to intrude more into coastal area. So deforestation of mangrove should be regularly monitored.

Keywords: indus delta, object based image analysis, soil salinity, thematic mapper

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Supriya Ambawat, Subaran Singh, C. Tara Satyavathi, B. S. Rajpurohit, Ummed Singh, Balraj Singh

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Pearl millet [Pennisetum glaucum (L.) R. Br.] is an important staple food of the arid and semiarid tropical regions of Asia, Africa, and Latin America. It is rightly termed as nutricereal as it has high nutrition value and a good source of carbohydrate, protein, fat, ash, dietary fiber, potassium, magnesium, iron, zinc, etc. Pearl millet has low prolamine fraction and is gluten free which is useful for people having a gluten allergy. It has several health benefits like reduction in blood pressure, thyroid, diabe¬tes, cardiovascular and celiac diseases but its direct consumption as food has significantly declined due to several reasons. Keeping this in view, it is important to reorient the ef¬forts to generate demand through value-addition and quality improvement and create awareness on the nutritional merits of pearl millet. In India, through Indian Council of Agricultural Research-All India Coordinated Research Project on Pearl millet, multilocational coordinated trials for developed hybrids were conducted at various centers. The gene banks of pearl millet contain varieties with high levels of iron and zinc which were used to produce new pearl millet varieties with elevated iron levels bred with the high‐yielding varieties. Thus, using breeding approaches and biochemical analysis, a total of 167 hybrids and 61 varieties were identified and released for cultivation in different agro-ecological zones of the country which also includes some biofortified hybrids rich in Fe and Zn. Further, using several biotechnological interventions such as molecular markers, next-generation sequencing (NGS), association mapping, nested association mapping (NAM), MAGIC populations, genome editing, genotyping by sequencing (GBS), genome wide association studies (GWAS) advancement in millet improvement has become possible by identifying and tagging of genes underlying a trait in the genome. Using DArT markers very high density linkage maps were constructed for pearl millet. Improved HHB67 has been released using marker assisted selection (MAS) strategies, and genomic tools were used to identify Fe-Zn Quantitative Trait Loci (QTL). The draft genome sequence of millet has also opened various ways to explore pearl millet. Further, genomic positions of significantly associated simple sequence repeat (SSR) markers with iron and zinc content in the consensus map is being identified and research is in progress towards mapping QTLs for flour rancidity. The sequence information is being used to explore genes and enzymatic pathways responsible for rancidity of flour. Thus, development and application of several biotechnological approaches along with biofortification can accelerate the genetic gain targets for pearl millet improvement and help improve its quality.

Keywords: Biotechnological approaches, genomic tools, malnutrition, MAS, nutricereal, pearl millet, sequencing.

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Authors: Bsma Adel Bany Mohammad

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The University campuses are a small city containing basic city functions such as educational spaces, accommodations, services and transportation. They are spaces of functional and social life with different activities, different occupants. The campus designed and transformed like cities so both experienced and memorized in same way. Campus memory is the ability of individuals to maintain and reveal the spatial components of designed physical spaces, which form the understandings, experiences, sensations of the environment in all. ‘Cognitive mapping’ is used to decode the physical interaction and emotional relationship between individuals and the city; Cognitive maps are created graphically using geometric and verbal elements on paper by remembering the images of the Urban Environment. In this study, to determine the emotional urban identity belonging to Jordan University of science and technology Campus, architecture students Asked to identify the areas they interact with in the campus by drawing a cognitive map. ‘Campus memory items’ are identified by analyzing the cognitive maps of the campus, then the spatial identity result of such data. The analysis based on the five basic elements of Lynch: paths, districts, edges, nodes, and landmarks. As a result of this analysis, it found that Spatial Identity constructed by the shared elements of the maps. The memory of most students listed the gates structure- which is a large desirable structure, located at the main entrances within the campus defined as major landmarks, then the square spaces defined as nodes, in addition to both stairs and corridors defined as paths. Finally, the districts, edges of educational buildings and service spaces are listed correspondingly in cognitive maps. Findings suggest that the spatial identity of the campus design is related mainly to the gates structures, squares and stairs.

Keywords: cognitive maps, university campus, urban memory, identity

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

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Authors: Raheleh Farzanmanesh, Christopher J. Weston

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Mangroves are forest ecosystems located in the inter-tidal regions of tropical and subtropical coastlines that provide many valuable economic and ecological benefits for millions of people, such as preventing coastal erosion, providing breeding, and feeding grounds, improving water quality, and supporting the well-being of local communities. In addition, mangroves capture and store high amounts of carbon in biomass and soils that play an important role in combating climate change. The decline in mangrove area has prompted government and private sector interest in mangrove conservation and restoration projects to achieve multiple Sustainable Development Goals, from reducing poverty to improving life on land. Mangrove aboveground biomass plays an essential role in the global carbon cycle, climate change mitigation and adaptation by reducing CO2 emissions. However, little information is available about the effectiveness of mangrove sustainable management on mangrove change area and aboveground biomass (AGB). Here, we proposed a method for mapping, modeling, and assessing mangrove area and AGB in two Global Environment Facility (GEF) blue forests projects based on Sentinel-2 Level 1C imagery during their conservation lifetime. The SVR regression model was used to estimate AGB in Tahiry Honko project in Madagascar and the Abu Dhabi Blue Carbon Demonstration Project (Abu Dhabi Emirates. The results showed that mangrove forests and AGB declined in the Tahiry Honko project, while in the Abu Dhabi project increased after the conservation initiative was established. The results provide important information on the impact of mangrove conservation activities and contribute to the development of remote sensing applications for mapping and assessing mangrove forests in blue carbon initiatives.

Keywords: blue carbon, mangrove forest, REDD+, aboveground biomass, Sentinel-2

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Authors: Eric Lee G. Escobedo-Wu, Nidhi Rohatgi, Fouzel Dhebar

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It is challenging for patients to navigate through healthcare systems after-hours. This leads to delays in care, patient/provider dissatisfaction, inappropriate resource utilization, readmissions, and higher costs. It is important to provide patients and providers with effective clinical decision-making tools to allow seamless connectivity and coordinated care. In August 2015, patient-centric Stanford Health Care established Clinical Advice Services (CAS) to provide clinical decision support after-hours. CAS is founded on key Lean principles: Value stream mapping, empathy mapping, waste walk, takt time calculations, standard work, plan-do-check-act cycles, and active daily management. At CAS, Clinical Assistants take the initial call and manage all non-clinical calls (e.g., appointments, directions, general information). If the patient has a clinical symptom, the CAS nurses take the call and utilize standardized clinical algorithms to triage the patient to home, clinic, urgent care, emergency department, or 911. Nurses may also contact the on-call physician based on the clinical algorithm for further direction and consultation. Since August 2015, CAS has managed 228,990 calls from 26 clinical specialties. Reporting is built into the electronic health record for analysis and data collection. 65.3% of the after-hours calls are clinically related. Average clinical algorithm adherence rate has been 92%. An average of 9% of calls was escalated by CAS nurses to the physician on call. An average of 5% of patients was triaged to the Emergency Department by CAS. Key learnings indicate that a seamless connectivity vision, cascading, multidisciplinary ownership of the problem, and synergistic enterprise improvements have contributed to this success while striving for continuous improvement.

Keywords: after hours phone calls, clinical advice services, nurse triage, Stanford Health Care

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Authors: L. Nahimana

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The eastern edge of the East African Rift in Burundi shows many mass movement phenomena corresponding to landslides, mudflow, debris flow, spectacular erosion (mega-gully), flash floods and alluvial deposits. These phenomena usually occur during the rainy season. Their extent and consecutive damages vary widely. To manage these phenomena, it is necessary to adopt a methodological approach of their mapping with a structured database. The elements for this database are: three-dimensional extent of the phenomenon, natural causes and conditions (geological lithology, slope, weathering depth and products, rainfall patterns, natural environment) and the anthropogenic factors corresponding to the various human activities. The extent of the area provides information about the possibilities and opportunities for mitigation technique. The lithological nature allows understanding the influence of the nature of the rock and its structure on the intensity of the weathering of rocks, as well as the geotechnical properties of the weathering products. The slope influences the land stability. The intensity of annual, monthly and daily rainfall helps to understand the conditions of water saturation of the terrains. Certain natural circumstances such as the presence of streams and rivers promote foot slope erosion and thus the occurrence and activity of mass movements. The construction of some infrastructures such as new roads and agglomerations deeply modify the flow of surface and underground water followed by mass movements. Using geospatial data selected on the East African Rift in Burundi, it is presented case of mass movements illustrating the nature, importance, various factors and the extent of the damages. An analysis of these elements for each hazard can guide the options for mitigation of the phenomenon and its consequences.

Keywords: mass movement, landslide, mudflow, debris flow, spectacular erosion, mega-gully, flash flood, alluvial deposit, East African rift, Burundi

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Valeria Cotza

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School drop-out is a multifactorial phenomenon that in Italy concerns all those underage students who, at different school stages (up to 16 years old) or training (up to 18 years old), manifest educational difficulties from dropping out of compulsory education without obtaining a qualification to repetition rates and absenteeism. From the 1980s to the 2000s, there was a progressive attenuation of the economic and social model towards a multifactorial reading of the phenomenon, and the European Commission noted the importance of learning about the phenomenon through approaches able to integrate large-scale quantitative surveys with qualitative analyses. It is not a matter of identifying the contextual factors affecting the phenomenon but problematising them by means of systemic and comprehensive in-depth analysis. So, a privileged point of observation and field of intervention are those schools that propose alternative models of teaching and learning to the traditional ones, such as popular and second-chance schools. Alternative schools and interventions grew in these years in Europe as well as in the US and Latin America, working in the direction of greater equity to create the conditions (often absent in conventional schools) for everyone to achieve educational goals. Against extensive Anglo-Saxon and US literature on this topic, there is yet no unambiguous definition of alternative education, especially in Europe, where second-chance education has been most studied. There is little literature on a second chance in Italy and almost none on alternative education (with the exception of method schools, to which in Italy the concept of “alternative” is linked). This research aims to fill the gap by systematically surveying the alternative interventions in the area and beginning to explore some models of popular and second-chance schools and experiences through a mixed methods approach. So, the main research objectives concern the spread of alternative education in the Lombardy region, the main characteristics of these schools and interventions, and their effectiveness in terms of students’ well-being and school results. This paper seeks to answer the first point by presenting the preliminary results of the first phase of the project dedicated to mapping. Through the Google Forms platform, a questionnaire is being distributed to all schools in Lombardy and some schools in the rest of Italy to map the presence of alternative schools and interventions and their main characteristics. The distribution is also taking place thanks to the support of the Milan Territorial and Lombardy Regional School Offices. Moreover, other social realities outside the school system (such as cooperatives and cultural associations) can be questioned. The schools and other realities to be questioned outside Lombardy will also be identified with the support of INDIRE (Istituto Nazionale per Documentazione, Innovazione e Ricerca Educativa, “National Institute for Documentation, Innovation and Educational Research”) and based on existing literature and the indicators of “Futura” Plan of the PNRR (Piano Nazionale di Ripresa e Resilienza, “National Recovery and Resilience Plan”). Mapping will be crucial and functional for the subsequent qualitative and quantitative phase, which will make use of statistical analysis and constructivist grounded theory.

Keywords: school drop-out, alternative education, popular and second-chance schools, map

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Authors: B. Mendonça, D. Sandwell

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The Metropolitan Region of Sao Paulo (MRSP) has suffered from serious water scarcity. Consequently, the most convenient solution has been building wells to extract groundwater from local aquifers. However, it requires constant vigilance to prevent over extraction and future events that can pose serious threat to the population, such as subsidence. Radar imaging techniques (InSAR) have allowed continuous investigation of such phenomena. The analysis of data in the present study consists of 23 SAR images dated from October 2007 to March 2011, obtained by the ALOS-1 spacecraft. Data processing was made with the software GMTSAR, by using the InSAR technique to create pairs of interferograms with ground displacement during different time spans. First results show a correlation between the location of 102 wells registered in 2009 and signals of ground displacement equal or lower than -90 millimeters (mm) in the region. The longest time span interferogram obtained dates from October 2007 to March 2010. As a result, from that interferogram, it was possible to detect the average velocity of displacement in millimeters per year (mm/y), and which areas strong signals have persisted in the MRSP. Four specific areas with signals of subsidence of 28 mm/y to 40 mm/y were chosen to investigate the phenomenon: Guarulhos (Sao Paulo International Airport), the Greater Sao Paulo, Itaquera and Sao Caetano do Sul. The coverage area of the signals was between 0.6 km and 1.65 km of length. All areas are located above a sedimentary type of aquifer. Itaquera and Sao Caetano do Sul showed signals varying from 28 mm/y to 32 mm/y. On the other hand, the places most likely to be suffering from stronger subsidence are the ones in the Greater Sao Paulo and Guarulhos, right beside the International Airport of Sao Paulo. The rate of displacement observed in both regions goes from 35 mm/y to 40 mm/y. Previous investigations of the water use at the International Airport highlight the risks of excessive water extraction that was being done through 9 deep wells. Therefore, it is affirmed that subsidence events are likely to occur and to cause serious damage in the area. This study could show a situation that has not been explored with proper importance in the city, given its social and economic consequences. Since the data were only available until 2011, the question that remains is if the situation still persists. It could be reaffirmed, however, a scenario of risk at the International Airport of Sao Paulo that needs further investigation.

Keywords: ground subsidence, Interferometric Satellite Aperture Radar (InSAR), metropolitan region of Sao Paulo, water extraction

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Authors: Mohamed F. Sadek, Safaa M. Hassan, Safwat S. Gabr

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Several alteration zones hosting gold mineralization are wide spreading in the South Eastern Desert of Egypt where gold has been mined from many localities since the time of the Pharaohs. The Sukkari is the only mine currently producing gold in the Eastern Desert of Egypt. Therefore, it is necessary to conduct more detailed studies on these locations using modern exploratory methods. The remote sensing plays an important role in lithological mapping and detection of associated hydrothermal mineralization particularly the exploration of gold mineralization. This study is focused on three localities in South Eastern Desert of Egypt, namely Beida, Defiet and Hoteib-Eiqat aiming to detect the gold-bearing hydrothermal alteration zones using the integrated data of remote sensing, field study and mineralogical investigation. Generally, these areas are dominated by Precambrian basement rocks including metamorphic and magmatic assemblages. They comprise ophiolitic serpentinite-talc carbonate, island-arc metavolcanics which were intruded by syn to late orogenic mafic and felsic intrusions mainly gabbro, granodiorite and monzogranite. The processed data of Advanced Spaceborne Thermal Emission and Reflection (ASTER) and Landsat-8 images are used in the present study to map the gold bearing-hydrothermal alteration zones. Band rationing and principal component analysis techniques are used to discriminate the different lithologic units exposed in the studied three areas. Field study and mineralogical investigation have been used to verify the remote sensing data. This study concluded that, the integrated remote sensing data with geological, field and mineralogical investigations are very effective in lithological discrimination, detailed geological mapping and detection of the gold-bearing hydrothermal alteration zones. More detailed exploration for gold mineralization with the help of remote sensing techniques is recommended to evaluate its potentiality in the study areas.

Keywords: pan-african, Egypt, landsat-8; ASTER, gold, alteration zones

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Authors: Lukasz Grabowski, Tytus Tulwin, Michal Geca, P. Karpinski

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This paper presents the radial aircraft engine model which has been created in AVL Boost software. This model is a one-dimensional physical model of the engine, which enables us to investigate the impact of an ignition system design on engine performance (power, torque, fuel consumption). In addition, this model allows research under variable environmental conditions to reflect varied flight conditions (altitude, humidity, cruising speed). Before the simulation research the identifying parameters and validating of model were studied. In order to verify the feasibility to take off power of gasoline radial aircraft engine model, some validation study was carried out. The first stage of the identification was completed with reference to the technical documentation provided by manufacturer of engine and the experiments on the test stand of the real engine. The second stage involved a comparison of simulation results with the results of the engine stand tests performed on a WSK ’PZL-Kalisz’. The engine was loaded by a propeller in a special test bench. Identifying the model parameters referred to a comparison of the test results to the simulation in terms of: pressure behind the throttles, pressure in the inlet pipe, and time course for pressure in the first inlet pipe, power, and specific fuel consumption. Accordingly, the required coefficients and error of simulation calculation relative to the real-object experiments were determined. Obtained the time course for pressure and its value is compatible with the experimental results. Additionally the engine power and specific fuel consumption tends to be significantly compatible with the bench tests. The mapping error does not exceed 1.5%, which verifies positively the model of combustion and allows us to predict engine performance if the process of combustion will be modified. The next conducted tests verified completely model. The maximum mapping error for the pressure behind the throttles and the inlet pipe pressure is 4 %, which proves the model of the inlet duct in the engine with the charging compressor to be correct.

Keywords: 1D-model, aircraft engine, performance, validation

Procedia PDF Downloads 329

Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Cahya Wimar Wicaksono, Reynara Davin Chen, Alvian Kristianto Santoso

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Grasberg Cu-Au ore deposit as one of the biggest porphyry deposits located in Papua Province, Indonesia produced by several intrusion that restricted by Heavy Sulphide Zone (HSZ) in peripheral. HSZ is the rock that becomes the contact between Grassberg Igneous Complex (GIC) with sedimentary and igneous rock outside, which is rich in sulphide minerals such as pyrite ± pyrrhotite. This research is to obtain the characteristic of HSZ based on geotechnical, geochemical and mineralogy aspect and those implication for daily mining operational activities. Method used in this research are geological and alteration mapping, core logging, FAA (Fire Assay Analysis), AAS (Atomic absorption spectroscopy), RQD (Rock Quality Designation) and rock water content. Data generated from methods among RQD data, mineral composition and grade, lithological and structural geology distribution in research area. The mapping data show that HSZ material characteristics divided into three type based on rocks association, there are near igneous rocks, sedimentary rocks and on HSZ area. And also divided based on its location, north and south part of research area. HSZ material characteristic consist of rock which rich of pyrite ± pyrrhotite, and RQD range valued about 25%-100%. Pyrite ± pyrrhotite which outcropped will react with H₂O and O₂ resulting acid that generates corrosive effect on steel wire and rockbolt. Whereas, pyrite precipitation proses in HSZ forming combustible H₂S gas which is harmful during blasting activities. Furthermore, the impact of H₂S gas in blasting activities is forming poison gas SO₂. Although HSZ high grade Cu-Au, however those high grade Cu-Au rich in sulphide components which is affected in flotation milling process. Pyrite ± pyrrhotite in HSZ will chemically react with Cu-Au that will settle in milling process instead of floating.

Keywords: combustible, corrosive, heavy sulphide zone, pyrite ± pyrrhotite

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Authors: Ravi Ande, Mousumi Hazari

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One of the common geophysical techniques for mapping subsurface geo-electrical structures, extensive hydro-geological research, and engineering and environmental geophysics applications is the use of time domain electromagnetic (TDEM)/transient electromagnetic (TEM) soundings. A large transmitter loop for energising the ground and a small receiver loop or magnetometer for recording the transient voltage or magnetic field in the air or on the surface of the earth, with the receiver at the center of the loop or at any random point inside or outside the source loop, make up a large loop TEM system. In general, one can acquire data using one of the configurations with a large loop source, namely, with the receiver at the center point of the loop (central loop method), at an arbitrary in-loop point (in-loop method), coincident with the transmitter loop (coincidence-loop method), and at an arbitrary offset loop point (offset-loop method), respectively. Because of the mathematical simplicity associated with the expressions of EM fields, as compared to the in-loop and offset-loop systems, the central loop system (for ground surveys) and coincident loop system (for ground as well as airborne surveys) have been developed and used extensively for the exploration of mineral and geothermal resources, for mapping contaminated groundwater caused by hazardous waste and thickness of permafrost layer. Because a proper analytical expression for the TEM response over the layered earth model for the large loop TEM system does not exist, the forward problem used in this inversion scheme is first formulated in the frequency domain and then it is transformed in the time domain using Fourier cosine or sine transforms. Using the EMLCLLER algorithm, the forward computation is initially carried out in the frequency domain. As a result, the EMLCLLER modified the forward calculation scheme in NLSTCI to compute frequency domain answers before converting them to the time domain using Fourier Cosine and/or Sine transforms.

Keywords: time domain electromagnetic (TDEM), TEM system, geoelectrical sounding structure, Fourier cosine

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Authors: Stanzin Gawa, Nalini Ranjan Kumar, Gohar Bilal Wani, Vinay Maruti Hatte, A. Vinay

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Rainbow trout (Oncorhynchus mykiss) and Brown trout (Salmo trutta fario) are the two species of trout which were once introduced by British in waters of Kashmir has well adapted to favorable climatic conditions. Cold water fisheries are one of the emerging sectors in Kashmir valley and trout holds an important place Jammu and Kashmir fisheries. Realizing the immense potential of trout culture in Kashmir region, the state fisheries department started privatizing trout culture under the centrally funded scheme of RKVY in which they provide 80 percent subsidy for raceway construction and supply of feed and seed for the first year since 2009-10 and at present there are 362 private trout farms. To cater the growing demand for trout in the valley, it is important to understand the bottlenecks faced in the propagation of trout culture. Value chain analysis provides a generic framework to understand the various activities and processes, mapping and studying linkages is first step that needs to be done in any value chain analysis. In Kashmir, it is found that trout hatcheries play a crucial role in insuring the continuous supply of trout seed in valley. Feed is most limiting factor in trout culture and the farmer has to incur high cost in payment and in the transportation of feed from the feed mill to farm. Lack of aqua clinic in the Kashmir valley needs to be addressed. Brood stock maintenance, breeding and seed production, technical assistance to private farmer, extension services have to be strengthened and there is need to development healthier environment for new entrepreneurs. It was found that trout farmers do not avail credit facility as there is no well define credit scheme for fisheries in the state. The study showed weak institutional linkages. Research and development should focus more on applied science rather than basic science.

Keywords: trout, Kashmir, value chain, linkages, culture

Procedia PDF Downloads 395