Search results for: RGBI aerial imagery

Authors: Alexander B. Barker, Megan Parkin, Shreesh Sinha, Emma Wilson, Rachael L. Murray

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Objectives: Exposure to HFSS imagery is associated with consumption of foods high in fat, sugar, or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children’s television channels in the UK and the other of a selection of children’s programs available on video-on-demand (VOD) streaming sites. Design: Content analysis of three days’ worth of programs (including advertisements) on two popular children’s television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children’s programs available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Setting: United Kingdom, Participants: None. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, ‘Milkshake’ had a significantly higher proportion of programs/adverts which contained HFSS content than ‘CBeebies’. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programs containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children’s television channels and children's programs on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children’s television programs broadcast either on TV or VOD services are likely having an effect on HFSS consumption in children and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, epidemiology, obesity, content analysis

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Authors: Gebremedhin Kiros, Amba Shetty, Lakshman Nandagiri

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Soil erosion is a major threat to the sustainability of land and water resources in the catchment and there is a need to identify critical areas of erosion so that suitable conservation measures may be adopted. The present study was taken up to understand the temporal and spatial distribution of soil erosion and daily sediment yield in Geba catchment (5137 km2) located in the Northern Highlands of Ethiopia. Soil and Water Assessment Tool (SWAT) was applied to the Geba catchment using data pertaining to rainfall, climate, soils, topography and land use/land cover (LU/LC) for the historical period 2000-2013. LU/LC distribution in the catchment was characterized using LANDSAT satellite imagery and the GIS-based ArcSWAT version of the model. The model was calibrated and validated using sediment concentration measurements made at the catchment outlet. The catchment was divided into 13 sub-basins and based on estimated soil erosion, these were prioritized on the basis of susceptibility to soil erosion. Model results indicated that the average sediment yield estimated of the catchment was 12.23 tons/ha/yr. The generated soil loss map indicated that a large portion of the catchment has high erosion rates resulting in significantly large sediment yield at the outlet. Steep and unstable terrain, the occurrence of highly erodible soils and low vegetation cover appeared to favor high soil erosion. Results obtained from this study prove useful in adopting in targeted soil and water conservation measures and promote sustainable management of natural resources in the Geba and similar catchments in the region.

Keywords: Ethiopia, Geba catchment, MUSLE, sediment yield, SWAT Model

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Authors: Abubakar Muhammad Umar, Nur Adeela Yasid, Hassan Mohd Daud, Mohd Yunus Abd Shukor

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Glyphosate [N-(phosphonomethyl) glycine] is among the most broadly and generally recognised broad-spectrum herbicides used in agriculture due to its low cost and effectiveness in weed management. The pollution of glyphosate in the aquatic environment can be via water run-off from agricultural lands, or by spray drift, aerial spraying or due to industrial discharge, which may be seen as a threat to aquatic biota. Fish is one of the best organisms to study the toxicological aspects of glyphosate. A 49 days experiment was conducted under laboratory conditions to ascertain the effects of technical grade glyphosate on behaviour and histopathological conditions in the gills of red hybrid tilapia using a light inverted microscope. Air gasping, erratic swimming, fin movement, mucus secretion, hemorrhages, and loss of scales were observed as behavioural changes in the exposed fish. There was no histopathological complication observed in the gill of the control fish, but various levels of alterations were seen in the gills of the fish exposed to glyphosate herbicide. These include lifting of primary lamella, congestion of secondary lamella, as well as hyperplasia in both primary and secondary gill lamella, and hypertrophy of secondary gill lamella. Based on the findings of this study, glyphosate herbicide exerts behavioural and histopathological changes in the gill of red hybrid tilapia, and therefore, the fish is considered a good bioindicator in aquatic environment monitoring. Excessive usage of glyphosate herbicide near aquatic habitats should be discouraged.

Keywords: behavioural, histopathological, Oreochromis niloticus, glyphosate

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Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

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One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

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Authors: Bhogendra Mishra, Andy Nelson, Mirco Boschetti, Lorenzo Busetto, Alice Laborte

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Rice is grown on over 100 million hectares in almost every country of Asia. It is the most important staple crop for food security and has high economic and cultural importance in Asian societies. The combination of genetic diversity and management options, coupled with the large geographic extent means that there is a large variation in seasonality (when it is grown) and cropping intensity (how often it is grown per year on the same plot of land), even over relatively small distances. Seasonality and intensity can and do change over time depending on climatic, environmental and economic factors. Detecting where and when these changes happen can provide information to better understand trends in regional and even global rice production. Remote sensing offers a unique opportunity to estimate these trends. We apply the recently published PhenoRice algorithm to 14 years of moderate resolution remote sensing (MODIS) data (utilizing 250m resolution 16 day composites from Terra and Aqua) to estimate seasonality and cropping intensity per year and changes over time. We compare the results to the surveyed data collected by International Rice Research Institute (IRRI). The study results in a unique and validated dataset on the extent and change of extent, the seasonality and change in seasonality and the cropping intensity and change in cropping intensity between 2003 and 2016 for the Philippines. Observed trends and their implications for food security and trade policies are also discussed.

Keywords: rice, cropping intensity, moderate resolution remote sensing (MODIS), phenology, seasonality

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Jinny Hong, Jeanne C. Watson

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Three types of autobiographical memory recall -specific, episodic, and generic- were examined in relation to the quality of descriptions and in-session levels of emotional arousal. Correlational analyses and general estimating equation were conducted to test the relationships between 1) quality of descriptions and type of memory, 2) type of memory and emotional arousal, and 3) quality of descriptions and emotional arousal. The data was transcripts drawn from an archival randomized-control study comparing cognitive-behavioral therapy and emotion-focused therapy in a 16-week treatment for depression. Autobiographical memory recall segments were identified and sorted into three categories: specific, episodic, and generic. Quality of descriptions of these segments was then operationalized and measured using the Referential Activity Scale, and each memory segment was rated on four dimensions: concreteness, specificity, clarity, and overall imagery. Clients’ level of emotional arousal for each recall was measured using the Client’s Expression Emotion Scale. Contrary to the predictions, generic memories are associated with higher emotional arousal ratings and descriptive language ratings compared to specific memories. However, a positive relationship emerged between the quality of descriptions and expressed emotional arousal, indicating that the quality of descriptions in which memories are described in sessions is more important than the type of memory recalled in predicting clients’ level of emotional arousal. The results from this study provide a clearer understanding of the role of memory recall types and use of language in activating emotional arousal in psychotherapy sessions in a depressed sample.

Keywords: autobiographical memory recall, emotional arousal, psychotherapy for depression, quality of descriptions, referential activity

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Authors: Punitha Periyasamy, Mahalingam Sudalaimuthu, Sachikanta Nanda, Arasu Sundaram

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India holds 17.5% of the world’s population but has only 2% of the total geographical area of the world where 27.35% of the area is categorized as wasteland due to lack of or less groundwater. So there is a demand for excessive groundwater for agricultural and non agricultural activities to balance its growth rate. With this in mind, an attempt is made to find the groundwater potential zone in Gomukhi river sub basin of Vellar River basin, TamilNadu, India covering an area of 1146.6 Sq.Km consists of 9 blocks from Peddanaickanpalayam to Villupuram fall in the sub basin. The thematic maps such as Geology, Geomorphology, Lineament, Landuse, and Landcover and Drainage are prepared for the study area using IRS P6 data. The collateral data includes rainfall, water level, soil map are collected for analysis and inference. The digital elevation model (DEM) is generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area is obtained. ArcGIS 10.1 acts as a powerful spatial analysis tool to find out the ground water potential zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their influence to increase the water level in the ground. The potential zones in the study area are classified viz., Very Good, Good, Moderate, Poor with its aerial extent of 15.67, 381.06, 575.38, 174.49 Sq.Km respectively.

Keywords: ArcGIS, DEM, groundwater, recharge, weighted overlay

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Authors: Quirijn Menken

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Menken, Q. Author  Constellating Images Abstract—We live in a predominantly visual era. Vastly expanded quantities of imagery influence us on a daily basis, in contrast to earlier days where the textual prevailed. The increasing producing and reproducing of images continuously compete for our attention. As such, how we perceive images and in what way images are framed or mediate our beliefs, has become of even greater importance than ever before. Especially in art education a critical awareness and approach of images as part of visual culture is of utmost importance. The Bilderatlas operates as a mediation, and offers new Ways of Seeing and knowing. It is mainly known as result of the ground-breaking work of the cultural theorist Aby Warburg, who intended to present an art history without words. His Mnemosyne Bilderatlas shows how the arrangement of images - and the interstices between them, offers new perspectives and ways of seeing. The Atlas as a medium to critically address Visual Culture is also practiced by the German artist Gerhard Richter, and it is in written form used in the Passagen Werk of Walter Benjamin. In order to examine the use of the Bilderatlas as a tool in art education, several experiments with art students have been conducted. These experiments have lead to an exploration of different Pedagogies, which help to offer new perspectives and trajectories of learning. To use the Bilderatlas as a tool to develop criticality towards Visual Culture, I developed and tested a new pedagogy; a Pedagogy of Difference and Repetition, based on the philosophy of Gilles Deleuze. Furthermore, in offering a new pedagogy - based on the rhizomatic work of Gilles Deleuze – the Bilderatlas as a tool to develop criticality has found a firm basis. Keywords—Art Education, Walter Benjamin, Bilderatlas, Gilles Deleuze, Difference and Repetition, Pedagogy, Rhizomes, Visual Culture,

Keywords: Art Education, Bilderatlas, Pedagogy, Aby Warburg

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Reza Dehghani Bidgoli

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Information on different rangeland plants’ nutritive values at various phonological stages is important in rangelands management. This information helps rangeland managers to choose proper grazing times to achieve higher animal performance without detrimental effects on the rangeland vegetations. Effects of various plant parts’ phonological stages and vegetation types on reserve carbohydrates and forage quality indicators were investigated during the 2009 and 2010. Plant samples were collected in a completely randomized block (CRB) design. The species included, grasses (Secale montanum and Festuco ovina), forbs (Lotus corniculatus and Sanguisorba minor), and shrubs (Kochia prosterata and Salsola rigida). Aerial plant parts’ samples were oven-dried at 80oC for 24 hours, then analyzed for soluble carbohydrates, crude protein (CP), acid detergent fiber (ADF), dry matter digestible (DMD), and metabolizable energy (ME). Results showed that plants at the seedling stage had more reserve carbohydrates and from the three vegetation types (grass, forbs, and shrub), forbs contained more soluble carbohydrates compared to the other two (grasses and shrubs). Differences in soluble carbohydrate contents of different species at various phonological stages in 2 years were statistically significant. The forage quality indicators (CP, ADF, DMD, and ME) in different species, in different vegetation types, in the 2 years were statistically significant, except for the CP.

Keywords: grazing, soluble carbohydrate, protein, fiber, metabolizeable energy

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Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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Authors: Karima Sekkoum Abdelkrim Cheriti, Leila Feguigui

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Algeria has a large plant biodiversity accounting more than 4125 species (123 Families) and is endowed with resources of medicinal plants growing on various bioclimatic zones from subhumide to semi-arid and Saharan. On the other hand, the ethnopharmacology investigation remains the principal way to improve, evaluate, and finding bioactive substances derived from medicinal plants. In continuation of our works in Saharan ethpharmacopeae and phytochemistry of Saharan medicinal plants, we focus our attention on the importance of local ethnopharmacology especially to treat gastro-intestinal disorders in the south west of Algeria (El Baydh, Naama and Bechar region) as platform for bioactive substances discovery and further development. Our present investigation deals with an ethnopharmacological study on medicinal plants used for the treatment of gastro-intestinal disorders in the south west of Algeria. The study presents the uses of plants in local traditional herbal medicines, determines the homogeneity of informant traditional knowledge and the preferred medicinal plants used to treat gastro-intestinal disorders. The results indicated that Asteraceae and Lamiaceae are the most locally used families and medicines were prepared in the form of powder or infusion and used orally. Aerial parts were the most frequently used plant part. Thus, the results can be used as platform for bioactive substances discovery and further development especially for the preferred plant species used in the treatment of gastro-intestinal disorders.

Keywords: ethnopharmacology, gastro-intestinal, phytochemical, South Algeria, Sahara, endemic species

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Authors: Wambugu Naftaly, Ruisheng Wang, Zhijun Wang

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Models based on convolutional neural networks (CNNs), in conjunction with Transformer, have excelled in semantic segmentation, a fundamental task for intelligent Earth observation using remote sensing (RS) imagery. Nonetheless, tokenization in the Transformer model undermines object structures and neglects inner-patch local information, whereas CNNs are unable to simulate global semantics due to limitations inherent in their convolutional local properties. The integration of the two methodologies facilitates effective global-local feature aggregation and interactions, potentially enhancing segmentation results. Inspired by the merits of CNNs and Transformers, we introduce a layer-level feature aggregation network (LLFA-Net) to address semantic segmentation of fine-resolution remote sensing (FRRS) images for land cover classification. The simple yet efficient system employs a transposed unit that hierarchically utilizes dense high-level semantics and sufficient spatial information from various encoder layers through a layer-level feature aggregation module (LLFAM) and models global contexts using structured Transformer blocks. Furthermore, the decoder aggregates resultant features to generate rich semantic representation. Extensive experiments on two public land cover datasets demonstrate that our proposed framework exhibits competitive performance relative to the most recent frameworks in semantic segmentation.

Keywords: land cover mapping, semantic segmentation, remote sensing, vision transformer networks, deep learning

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Authors: Edoardo Lomi

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A problem of central interest in anthropology concerns the ethnographic displacement of modernity’s conceptual sovereignty over that of native collectives worldwide. Part of this critical project has been the association of Western modernity with a dualist, naturalist ontology. Despite its demonstrated value for comparative work, this association often comes at the cost of reproducing ideas that lack an empirical ethnographic basis. This paper proposes a way forward by bringing to bear some of the results produced by an ethnographic study of a village in Wiltshire, South England. Due to its picturesque qualities, this village has served for decades as a ready-made set for fantasy movies and a backdrop to fictional stories. These forms of mediation have in turn generated some apparent paradoxes, such as fictitious characters that affect actual material changes, films that become more real than history, and animated stories that, while requiring material grounds to unfold, inhabit a time and space in other respects distinct from that of material processes. Drawing on ongoing fieldwork and interviews with locals and tourists, this paper considers the ways villagers engage with fiction as part of their everyday lives. The resulting image is one of convergence, in the same landscape, of people and things having different ontological status. This study invites reflection on the implications of this image for diversifying our imagery of Western lifeworlds. To this end, the notion of ‘real fictions’ is put forth, connecting the ethnographic blurring of modernist distinctions–such as sign and signified, mind and matter, materiality and immateriality–with discussions on anthropology’s own reliance on fictions for critical comparative work.

Keywords: England, ethnography, landscape, modernity, mediation, ontology, post-structural theory

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Authors: Johnson Okoduwa Imumbhon, Mohammad Didarul Alam, Yiding Cao

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Structural analyses are commonly employed to test the integrity of aircraft component systems in the design stage to demonstrate the capability of the structural components to withstand what it was designed for, as well as to predict potential failure of the components. The analyses are also essential for weight minimization and selecting the most resilient materials that will provide optimal outcomes. This research focuses on testing the structural nature of a high-lift low Reynolds number airfoil profile design, the Selig S1223, under certain loading conditions for a drone model application. The wing (ribs, spars, and skin) of the drone model was made of carbon fiber-reinforced polymer and designed in SolidWorks, while the finite element analysis was carried out in ANSYS mechanical in conjunction with the lift and drag forces that were derived from the aerodynamic airfoil analysis. Additionally, modal analysis was performed to calculate the natural frequencies and the mode shapes of the wing structure. The structural strain and stress determined the minimal deformations under the wing loading conditions, and the modal analysis showed the prominent modes that were excited by the given forces. The research findings from the structural analysis of the S1223 high-lift airfoil indicated that it is applicable for use in an unmanned aerial vehicle as well as a novel reciprocating-airfoil-driven vertical take-off and landing (VTOL) drone model.

Keywords: CFRP, finite element analysis, high-lift, S1223, strain, stress, VTOL

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Authors: Su Nandar Tin, Wutjanun Muttitanon

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The availability of free global and historical satellite imagery provides a valuable opportunity for mapping and monitoring the year by year for the built-up area, constantly and effectively. Land distribution guidelines and identification of changes are important in preparing and reviewing changes in the ground overview data. This study utilizes Landsat images for thirty years of information to acquire significant, and land spread data that are extremely valuable for urban arranging. This paper is mainly introducing to focus the basic of extracting built-up area for the city development area from the satellite images of LANDSAT 5,7,8 and Sentinel 2A from USGS in every five years. The purpose analyses the changing of the urban built-up area according to the year by year and to get the accuracy of mapping built-up and bare land areas in studying the trend of urban built-up changes the periods from 1990 to 2020. The GIS tools such as raster calculator and built-up area modelling are using in this study and then calculating the indices, which include enhanced built-up and bareness index (EBBI), Normalized difference Built-up index (NDBI), Urban index (UI), Built-up index (BUI) and Normalized difference bareness index (NDBAI) are used to get the high accuracy urban built-up area. Therefore, this study will point out a variable approach to automatically mapping typical enhanced built-up and bare land changes (EBBI) with simple indices and according to the outputs of indexes. Therefore, the percentage of the outputs of enhanced built-up and bareness index (EBBI) of the sentinel-2A can be realized with 48.4% of accuracy than the other index of Landsat images which are 15.6% in 1990 where there is increasing urban expansion area from 43.6% in 1990 to 92.5% in 2020 on the study area for last thirty years.

Keywords: built-up area, EBBI, NDBI, NDBAI, urban index

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Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

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Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

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Authors: Kechnit Djamel, Ammarri Abdelhadi, Raphael Tshimang, Mark Trrig

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One of the most important aspects of monitoring rivers is navigation. The variation of discharge in the river generally produces a change in available draft for a vessel, particularly in the low flow season, which can impact the navigable water path, especially when the water depth is less than the normal one, which allows safe navigation for boats. The water depth is related to the bathymetry of the channel as well as the discharge. For a seasonal update of the navigation maps, a daily discharge value is required. Many novel approaches based on earth observation and remote sensing have been investigated for large rivers. However, it should be noted that most of these approaches are not currently able to directly estimate river discharge. This paper discusses the application of remote sensing tools using the analysis of the reflectance value of MODIS imagery and is combined with field measurements for the estimation of discharge. This approach is applied in the lower reach of the Congo River (Pool Malebo) for the period between 2019 and 2021. The correlation obtained between the observed discharge observed in the gauging station and the reflectance ratio time series is 0.81. In this context, a Discharge Reflectance Model (DRM) was developed to express discharge as a function of reflectance. This model introduces a non-contact method that allows discharge monitoring using earth observation. DRM was validated by field measurements using ADCP, in different sections on the Pool Malebo, over two different periods (dry and wet seasons), as well as by the observed discharge in the gauging station. The observed error between the estimated and measured discharge values ranges from 1 to 8% for the ADCP and from (1% to 11%) for the gauging station. The study of the uncertainties will give us the possibility to judge the robustness of the DRM.

Keywords: discharge monitoring, navigation, MODIS, empiric, ADCP, Congo River

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Authors: Abdelrahman Elsehsah

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The main objective of this study is to assess changes in the water capacity of Aswan High Dam Lake (AHDL) caused by evaporation and seepage losses. To achieve this objective, a comprehensive methodology was employed. The methodology involves acquiring Sentinel-3 imagery and extracting the surface area of the lake using remote sensing techniques. Using water areas calculated from sentinel images, collected field data, and the lake’s water balance equation, monthly evaporation and seepage losses were estimated for the years 2021 and 2022. Based on the water balance method results, the average monthly evaporation losses for the year 2021 were estimated to be around 1.41 billion cubic meters (Bm3), which closely matches the estimates provided by the Ministry of Water Resources and Irrigation (MWRI) annual reports (approximately 1.37 Bm3 in the same year). This means that the water balance method slightly overestimated the monthly evaporation losses by about 2.92%. Similarly, the average monthly seepage losses for the year 2022 were estimated to be around 0.005 Bm3, while the MWRI reports indicated approximately 0.0046 Bm3. By another means, the water balance method overestimated the monthly seepage losses by about 8.70%. Furthermore, the study found that the average monthly evaporation rate within AHDL was 210.88 mm/month, which closely aligns with the computed value of approximately 204.9 mm/month by AHDA. These findings indicated that the applied water balance method, utilizing remote sensing and field data, is a reliable tool for estimating monthly evaporation and seepage losses as well as monthly evaporation rates in AHDL.

Keywords: Aswan high dam lake, remote sensing, water balance equation, seepage loss, evaporation loss

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Authors: Muhammad Umair Mushtaq, Ameena Iqbal, Muhammad Aqib Hassan Ali Khan, Ismat Nawaz, Sohail Yousaf, Mazhar Iqbal

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Heavy metals are one of the priority pollutants as they pose serious health and environmental threats. They can be removed by various physiochemical methods but are costly and responsible for additional environmental problems. Bioremediation that exploits plants and their associated microbes have been referred as cost effective and environmental friendly technique. In this study, a pot experiment was conducted in a greenhouse to evaluate the potential of Celosia cristata and effects of bacteria, Pseudomonas japonica, and organic amendment moss/compost on tolerating/accumulating heavy metals. Two weeks old seedlings were transferred to soil in pots, and after four weeks they were inoculated with bacterial strain, while after growth of six weeks they were watered with a metal containing synthetic wastewater and were harvested after a growth period of nine weeks. After harvesting, morphological and physiological parameters and metal content of plants were measured. The results showed highest plant growth and biomass production in case of organic amendments while highest metal uptake has been found in non-amended pots. Positive controls have shown highest Pb uptake of 2900 mg/kg DW, while P. japonica amended pots have shown highest Cd, Cr, Ni and Cu uptake of 963.53, 1481.17, 1022.01 and 602.17 mg/kg DW, respectively. In conclusion organic amendments have strong impacts on growth enhancement while P. japonica enhances metal translocation and accumulation to aerial parts with little significant involvement in plant growth.

Keywords: ornamental plants, plant microbe interaction, amendments, bacteria

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Authors: Yanto Santosa, Yohanna Dalimunthe, Intan Purnamasari

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Expansion of Indonesia oil palm plantations has contributed significantly to the national revenue annually and has been able to absorb millions of workers. Behind all these positive contributions, such expansion was accused as the cause of the decline in wildlife populations such as mammal and herpetofauna. Research was carried out in 8 oil palm plantations in Riau Province of Indonesia from March to April 2016, to determine the impacts of oil palm plantations on mammal and herpetofauna biodiversity. Direct observation was conducted simultaneously equipped with camera traps placed (for mammal) on various land cover types. For mammals' survey, line transect method was used, and for herpetofauna, Visual Encounter Survey (VES) method was used. Landsat imagery was used to interpret land cover types 3 years prior to the establishment of the oil palm plantations. The study revealed that one year before the oil palm plantations was established, most the land covers were comprised of 49.96% rubber plantations, 35.99% secondary forest, 10.17% bare land, 3.03% shrubs and 0.84% mixed dryland farming-shrubs. Based on the number of species found, it was identified that on the average, mammal diversity in 4 of 8 oil palm plantations, showed a decrease by 14.29%-100%, whereas 2 plantations did not experienced any changes in the number of species and one plantation showed an increased in the number of mammal species. The plantations that experienced a reduction in the number of mammal’s diversity were previously dominated covered by secondary forest (40%) and rubber plantation (40%), while those experiencing no changes in the number of species were also dominated by secondary forest. The area with an increased number of mammal species was historically dominated by rubber plantation. On the contrary, significant results were shown for herpetofauna, where all study sites showed a sharp increase in the number of herpetofauna species, by 100%-225.00%.

Keywords: herpetofauna, impact, mammal, oil palm plantations

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Authors: Catalina Albornoz, Giacomo Barbieri

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Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: Mouffok Ahlem, Belhamra Mohamed, Mouffok Sihem

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The use of nitrogen fertilizers inevitable consequence, the increase in the nitrate content of water, which may contribute to the production of nitrite and the formation of carcinogenic nitrosamines. The nitrogen fertilizer may also affect the structure and function of the microbial community. And the fight against eutrophication of aquatic environments represents a cost to the student statements. The agronomic, ecological and economic legumes such as faba beans and alfalfa are not demonstrated, especially in the case of semi-arid and arid areas. Osmotic stress due to drought and / or salinity deficit, nutritional deficiencies is the major factors limiting symbiotic nitrogen fixation and productivity of pulses. To study the symbiotic nitrogen fixation in faba bean (Vicia faba L.) and alfalfa (Medicago sativa L.) in the region of Biskra, we used soil samples collected from 30 locations. This work has identified several issues of ecological and agronomic interest. Evaluation of symbiotic potential of soils in the region of Biskra; by trapping technique, show different levels of susceptibility to rhizobial microflora. The effectiveness of the rhizobial symbiosis in both legumes indicates that air dry biomass and the amount of nitrogen accumulated in the aerial part, depends mainly on the rate of nodulation and regardless of the species and locality. The correlation between symbiotic nitrogen fixation and some physico-chemical properties of soils shows that symbiotic nitrogen fixation in both legumes is strongly related to soil conditions of the soil. Salinity disrupts the physiological process of growth, development and more particularly that of the symbiotic fixation of atmospheric nitrogen. Against by phosphorus promotes rhizobial symbiosis.

Keywords: rhizobia, faba bean, alfalfa, salinity

Procedia PDF Downloads 460

Authors: Kimberly Joyce A. Roguis, Mica Lorraine L. Fernando, Alan Vito B. Macadangdang, Jennina Mari C. Mijares, Maria Carinnes A. Gonzalez

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The paper showcases the vulnerability of the tourism industry especially the inevitable occurrence of natural disasters, implicating the necessity for post-disaster analysis on tourist attractions. This study discusses the aftermath of the super typhoon ‘Yolanda’ incident in the locality of Coron Island, Palawan, assessing its general effect on the community and its tourism livelihood through the analysis of responses from key role-players in the tourism industry of the area gathered through semi-structured interviews and direct observation. The local government’s instigation of recovery programs to their locality has been a pivotal factor in reviving the vitality of their tourism industry and the involvement of the community has been the determining condition that shifted the industry towards revival a year after the incidence. The study illuminates the disaster mitigation processes in the local tourism livelihood perspective, predominantly the diving industry. It did not suffer physical damage to a great extent but was affected because of the public imagery the disaster brought upon. Collaboration between the local government and the community is the highlight of the research for they maneuvered recovery revealing that cooperation between these two parties bridged the correlation of recovery to tourism development. The disaster paved way to a stance towards promoting progressive tourism outlooks, raising awareness among the public and private sectors and re-assessment of the tourism vitality in their locality. The mayhem and destruction proved to be a liberating creative process to give way to progression and was deemed to be of high significance in the over-all tourism system process despite its impediments in the case of the tourism industry in Coron, Palawan.

Keywords: disaster recovery, tourism development, diving, Palawan

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Authors: Esma Hande Alıcı, Gülnur Arabacı

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Antioxidants are compounds or systems that can safely interact with free radicals and terminate the chain reaction before vital molecules are damaged. The anti-oxidative effectiveness of these compounds depends on their chemical characteristics and physical location within a food (proximity to membrane phospholipids, emulsion interfaces, or in the aqueous phase). Antioxidants (e.g., flavonoids, phenolic acids, tannins, vitamin C, vitamin E) have diverse biological properties, such as antiinflammatory, anti-carcinogenic and anti-atherosclerotic effects, reduce the incidence of coronary diseases and contribute to the maintenance of gut health by the modulation of the gut microbial balance. Plants are excellent sources of antioxidants especially with their high content of phenolic compounds. Raphanus raphanistrum L., the wild radish, is a flowering plant in the family Brassicaceae. It grows in Asia and Mediterranean region. It has been introduced into most parts of the world. It spreads rapidly, and is often found growing on roadsides or in other places where the ground has been disturbed. It is an edible plant, in Turkey its fresh aerial parts are mostly consumed as a salad with olive oil and lemon juice after boiled. The leaves of the plant are also used as anti-rheumatic in traditional medicine. In this study, we determined the antioxidant capacity of two different solvent fractions (methanol and ethyl acetate) obtained from Raphanus raphanistrum L. plant leaves. Antioxidant capacity of the plant was introduced by using three different methods: DPPH radical scavenging activity, CUPRAC (Cupric Ion Reducing Antioxidant Capacity) activity and Reducing power activity.

Keywords: antioxidant activity, antioxidant capacity, Raphanis raphanistrum L., wild radish

Procedia PDF Downloads 277

Authors: Rabie Fadil, Parshuram Aarotale, Shubha Majumder, Bijay Guargain

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Hemorrhage is the loss of blood from the circulatory system and leading cause of battlefield and postpartum related deaths. Early detection of hemorrhage remains the most effective strategy to reduce mortality rate caused by traumatic injuries. In this study, we investigated the physiological changes via non-invasive cardiac signals at rest and under different hemorrhage conditions simulated through graded lower-body negative pressure (LBNP). Simultaneous electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure (BP), impedance cardiogram (ICG), and phonocardiogram (PCG) were acquired from 10 participants (age:28 ± 6 year, weight:73 ± 11 kg, height:172 ± 8 cm). The LBNP protocol consisted of applying -20, -30, -40, -50, and -60 mmHg pressure to the lower half of the body. Beat-to-beat heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean aerial pressure (MAP) were extracted from ECG and blood pressure. Systolic amplitude (SA), systolic time (ST), diastolic time (DT), and left ventricle Ejection time (LVET) were extracted from PPG during each stage. Preliminary results showed that the application of -40 mmHg i.e. moderate stage simulated hemorrhage resulted significant changes in HR (85±4 bpm vs 68 ± 5bpm, p < 0.01), ST (191 ± 10 ms vs 253 ± 31 ms, p < 0.05), LVET (350 ± 14 ms vs 479 ± 47 ms, p < 0.05) and DT (551 ± 22 ms vs 683 ± 59 ms, p < 0.05) compared to rest, while no change was observed in SA (p > 0.05) as a consequence of LBNP application. These findings demonstrated the potential of cardiac signals in detecting moderate hemorrhage. In future, we will analyze all the LBNP stages and investigate the feasibility of other physiological signals to develop a predictive machine learning model for early detection of hemorrhage.

Keywords: blood pressure, hemorrhage, lower-body negative pressure, LBNP, machine learning

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Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

Procedia PDF Downloads 46

Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

Procedia PDF Downloads 402