Search results for: natural and geometric images

Authors: Anna Mucha, Ewa Wojtyna, Anita Pollak

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The environment in which an individual resides and observes may play a meaningful role in well-being and related constructs. Contact with nature may have a positive influence of natural environments on individuals, impacting mood and psychophysical sensations, such as pain relief. Conversely, urban settings, dominated by concrete elements, might lead to mood decline and heightened stress levels. Similarly, the situation may appear in the case of the perception of virtual environments. However, this is a topic that requires further exploration, especially in the context of relationships with pain. The aforementioned matters served as the basis for formulating and executing the outlined experimental research within the realm of environmental psychology, leveraging new technologies, notably virtual reality (VR), which is progressively gaining prominence in the domain of mental health. The primary objective was to investigate the impact of a simulated virtual environment, mirroring a natural setting abundant in greenery, on the perception of acute pain induced by thermal stimuli (high temperature) – encompassing intensity, unpleasantness, and pain tolerance. Comparative analyses were conducted between the virtual natural environment (intentionally constructed in the likeness of a therapeutic garden), virtual urban environment, and a control group devoid of virtual projections. Secondary objectives aimed to determine the mutual relationships among variables such as positive and negative emotions, preferences regarding virtual environments, sense of presence, and restorative experience in the context of the perception of presented virtual environments and induced thermal pain. The study encompassed 126 physically healthy Polish adults, distributing 42 individuals across each of the three comparative groups. Oculus Rift VR technology and the TSA-II neurosensory analyzer facilitated the experiment. Alongside demographic data, participants' subjective feelings concerning virtual reality and pain were evaluated using the Visual Analogue Scale (VAS), the original Restorative Experience in the Virtual World questionnaire (Doświadczenie Regeneracji w Wirtualnym Świecie), and an adapted Slater-Usoh-Steed (SUS) questionnaire. Results of statistical and psychometric analyses, such as Kruskal-Wallis tests, Wilcoxon tests, and contrast analyses, underscored the positive impact of the virtual natural environment on individual pain perception and mood. The virtual natural environment outperformed the virtual urban environment and the control group without virtual projection, particularly in subjective pain components like intensity and unpleasantness. Variables such as restorative experience, sense of presence and virtual environment preference also proved pivotal in pain perception and pain tolerance threshold alterations, contingent on specific conditions. This implies considerable application potential for virtual natural environments across diverse realms of psychology and related fields, among others as a supportive analgesic approach and a form of relaxation following psychotherapeutic sessions.

Keywords: environmental psychology, nature, acute pain, emotions, vitrual reality, virtual environments

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Authors: Jhuang Jin-Jhong, Hsieh Wei-Fan

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Climate change causes natural disasters persistently. Therefore, nowadays environmental planning objective tends to the issues of respecting nature and coexisting with nature. As a result, the natural environment analysis, e.g., the analysis of topography, soil, hydrology, climate, vegetation, is highly emphasized. On the other hand, Feng Shui has been a criterion of site selection for residence in Eastern since the ancient times and has had farther influence on site selection for castles and even for temples and tombs. The primary criterion of site selection is judging the quality of Long: mountain range, Sha: nearby mountains, Shui: hydrology, Xue: foundation, Xiang: aspect, which are similar to the environmental variables of mountain range, topography, hydrology and aspect. For the reason, a lot researchers attempt to probe into the connection between the criterion of Feng Shui and environmental planning factors. Most researches only discussed with the composition and theory of space of Feng Shui, but there is no research which explained Feng Shui through the environmental field. Consequently, this study reviewed the theory of Feng Shui through the environmental planning viewpoint and assembled essential composition factors of Feng Shui. The results of this study point. From literature review and comparison of theoretical meanings, we find that the ideal principles for planning the Feng Shui environment can also be used for environmental planning. Therefore, this article uses 12 ideal environmental features used in Feng Shui to contrast the natural aspects of the environment and make comparisons with previous research and classifies the environmental factors into climate, topography, hydrology, vegetation, and soil.

Keywords: the composition of Feng Shui, environmental planning, site selection, main components of the Feng Shui environment

Procedia PDF Downloads 509

Authors: Suzanne Strauss, Leandi Steenkamp

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The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

Procedia PDF Downloads 111

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: M. E. Abou-Hashem El Dib, M. K. Swailem, M. M. Metwally, A. I. El Awady

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This paper presents the effect of stiffeners on the behavior of slender steel I-beams. Nonlinear three dimensional finite element models are developed to represent the stiffened steel I-beams. The well established finite element (ANSYS 13.0) program is used to simulate the geometric and material nonlinear nature of the problem. Verification is achieved by comparing the obtained numerical results with the results of previous published experimental work. The parameters considered in the analysis are the horizontal stiffener's position and the horizontal stiffener's dimensions as well as the number of vertical stiffeners. The studied dimensions of the horizontal stiffeners include the stiffener width, the stiffener thickness and the stiffener length. The results of the achieved numerical parametric study for slender steel I-beams show the significant effect of stiffeners on the beam behavior and its failure load.

Keywords: beams, local buckling, slender, stiffener, thin walled section

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: Ali Nadi, Ali Edrissi

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Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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Authors: R. K. Apalowo, D. Chronopoulos

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A Finite Element (FE) based scheme is presented for quantifying guided wave interaction with Localised Nonlinear Structural Damage (LNSD) within structures of arbitrary layering and geometric complexity. The through-thickness mode-shape of the structure is obtained through a wave and finite element method. This is applied in a time domain FE simulation in order to generate time harmonic excitation for a specific wave mode. Interaction of the wave with LNSD within the system is computed through an element activation and deactivation iteration. The scheme is validated against experimental measurements and a WFE-FE methodology for calculating wave interaction with damage. Case studies for guided wave interaction with crack and delamination are presented to verify the robustness of the proposed method in classifying and identifying damage.

Keywords: layered structures, nonlinear ultrasound, wave interaction with nonlinear damage, wave finite element, finite element

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Authors: Seyed Mostafa Jafari Raad, Hassan Hassanzadeh

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Injection of impurities along with CO₂ into saline aquifers provides an exceptional prospect for low-cost carbon capture and storage technologies and can potentially accelerate large-scale implementation of geological storage of CO₂. We have conducted linear stability analyses and numerical simulations to investigate the effects of permitted impurities in CO₂ streams on the onset of natural convection and dynamics of subsequent convective mixing. We have shown that the rate of dissolution of an impure CO₂ stream with H₂S highly depends on the operating conditions such as temperature, pressure, and composition of impurity. Contrary to findings of previous studies, our results show that an impurity such as H₂S can potentially reduce the onset time of natural convection and can accelerate the subsequent convective mixing. However, at the later times, the rate of convective dissolution is adversely affected by the impurities. Therefore, the injection of an impure CO₂ stream can be engineered to improve the rate of dissolution of CO₂, which leads to higher storage security and efficiency. Accordingly, we have identified the most favorable CO₂ stream compositions based on the geophysical properties of target aquifers. Information related to the onset of natural convection such as the scaling relations and the most favorable operating conditions for CO₂ storage developed in this study are important in proper design, site screening, characterization and safety of geological storage. This information can be used to either identify future geological candidates for acid gas disposal or reviewing the current operating conditions of licensed injection sites.

Keywords: CO₂ storage, solubility trapping, convective dissolution, storage efficiency

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Authors: Anna Drabczyk, Sonia Kudlacik-Kramarczyk, Dagmara Malina, Bozena Tyliszczak, Agnieszka Sobczak-Kupiec

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Nowadays, nano-size materials are very popular group of materials among scientists. What is more, these materials find an application in a wide range of various areas. Therefore constantly increasing demand for nanomaterials including metallic nanoparticles such as silver of gold ones is observed. Therefore, new routes of their preparation are sought. Considering potential application of nanoparticles, it is important to select an adequate methodology of their preparation because it determines their size and shape. Among the most commonly applied methods of preparation of nanoparticles chemical and electrochemical techniques are leading. However, currently growing attention is directed into the biological or biochemical aspects of syntheses of metallic nanoparticles. This is associated with a trend of developing of new routes of preparation of given compounds according to the principles of green chemistry. These principles involve e.g. the reduction of the use of toxic compounds in the synthesis as well as the reduction of the energy demand or minimization of the generated waste. As a result, a growing popularity of the use of such components as natural plant extracts, infusions or essential oils is observed. Such natural substances may be used both as a reducing agent of metal ions and as a stabilizing agent of formed nanoparticles therefore they can replace synthetic compounds previously used for the reduction of metal ions or for the stabilization of obtained nanoparticles suspension. Methods that proceed in the presence of previously mentioned natural compounds are environmentally friendly and proceed without the application of any toxic reagents. Methodology: Presented research involves preparation of silver nanoparticles using selected plant extracts, e.g. artichoke extract. Extracts of natural origin were used as reducing and stabilizing agents at the same time. Furthermore, syntheses were carried out in the presence of additional polymeric stabilizing agent. Next, such features of obtained suspensions of nanoparticles as total antioxidant activity as well as content of phenolic compounds have been characterized. First of the mentioned studies involved the reaction with DPPH (2,2-Diphenyl-1-picrylhydrazyl) radical. The content of phenolic compounds was determined using Folin-Ciocalteu technique. Furthermore, an essential issue was also the determining of the stability of formed suspensions of nanoparticles. Conclusions: In the research it was demonstrated that metallic nanoparticles may be obtained using plant extracts or infusions as stabilizing or reducing agent. The methodology applied, i.e. a type of plant extract used during the synthesis, had an impact on the content of phenolic compounds as well as on the size and polydispersity of obtained nanoparticles. What is more, it is possible to prepare nano-size particles that will be characterized by properties desirable from the viewpoint of their potential application and such an effect may be achieved with the use of non-toxic reagents of natural origin. Furthermore, proposed methodology stays in line with the principles of green chemistry.

Keywords: green chemistry principles, metallic nanoparticles, plant extracts, stabilization of nanoparticles

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

Procedia PDF Downloads 117

Authors: Namubiru Zula, Janice Desire Busingue

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Pro-active educational approaches have lately been adapted Globally in the Conservation of Natural Resources. This led to the introduction of the co-management system, which worked for some European Countries on the conservation of sharks and other Natural resources. However, this approach has drastically failed in the Fishery sector on Lake Victoria; and the punitive education approach has been re-instated. Literature is readily available about the punitive educational approaches and scanty with the pro-active one. This article analyses the pro-active approach adopted by the Department of Fisheries for the orientation of BMU leaders in a co-management system. The study is interpreted using the social constructivist lens for co-management of the fishery resource to ensure that fishers are also back to fishing sustainably. It highlights some of the education methods used, methodological challenges that included the power and skills gap of the facilitators and program designers, and some implications to practice.

Keywords: beach management units, fishers, education methods, proactive approach, punitive approach

Procedia PDF Downloads 123

Authors: Aziza Ben Halima, Julien Bert, Dimitris Visvikis

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In this paper, we propose designing and evaluating a parallel co-manipulated robot dedicated to low-dose-rate prostate brachytherapy. We developed 6 degrees of freedom compact and lightweight robot easy to install in the operating room thanks to its parallel design. This robotic system provides a co-manipulation allowing the surgeon to keep control of the needle’s insertion and consequently to improve the acceptability of the plan for the clinic. The best dimension’s configuration was solved by calculating the geometric model and using an optimization approach. The aim was to ensure the whole coverage of the prostate volume and consider the allowed free space around the patient that includes the ultrasound probe. The final robot dimensions fit in a cube of 300 300 300 mm³. A prototype was 3D printed, and the robot workspace was measured experimentally. The results show that the proposed robotic system satisfies the medical application requirements and permits the needle to reach any point within the prostate.

Keywords: medical robotics, co-manipulation, prostate brachytherapy, optimization

Procedia PDF Downloads 207

Authors: Nazlina Shaari

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Sustainability is economic, social and environmental systems that make up the community in providing a healthy, productive, meaningful life for all community residents, present and future. The environmental profile of goods and services that satisfy our individual and societal needs were shaped by design activities. The integration of environmental aspect of product design, especially in textiles present much confusion surrounds the incorporation of environmental objectives into the design process. This paper explores the effective use of waste materials that can contribute to the development of more environmentally responsible practice in textile sector. It introduces key elements of the ecological approach and innovative ideas from waste to wealth. The paper focuses on the potential methods of utilizing sago residue as a natural colour enhancer in natural dyeing process. It will discover the potential of waste materials to be fully utilized to attempt to make the production of that textile more environmentally friendly.

Keywords: sustainability, textiles, waste materials, environmentally friendly

Procedia PDF Downloads 319

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: Tahir Ali Akbar, Hirra Jabbar

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Land cover change analysis plays a significant role in understanding the trends of urban sprawl and land use transformation due to anthropogenic activities. In this study, the spatio-temporal dynamics of major land covers were analyzed in the last twenty years (1988-2016) for District Lahore located in the Punjab Province of Pakistan. The Landsat satellite imageries were downloaded from USGS Global Visualization Viewer of Earth Resources Observation and Science Center located in Sioux Falls, South Dakota USA. The imageries included: (i) Landsat TM-5 for 1988 and 2001; and (ii) Landsat-8 OLI for 2016. The raw digital numbers of Landsat-5 images were converted into spectral radiance and then planetary reflectance. The digital numbers of Landsat-8 image were directly converted into planetary reflectance. The normalized difference vegetation index (NDVI) was used to classify the processed images into six major classes of water, buit-up, barren land, shrub and grassland, sparse vegetation and dense vegetation. The NDVI output results were improved by visual interpretation using high-resolution satellite imageries. The results indicated that the built-up areas were increased to 21% in 2016 from 10% in 1988. The decrease in % areas was found in case of water, barren land and shrub & grassland. There were improvements in percentage of areas for the vegetation. The increasing trend of urban sprawl for Lahore requires implementation of GIS based spatial planning, monitoring and management system for its sustainable development.

Keywords: land cover changes, NDVI, remote sensing, urban sprawl

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Authors: H. Mat Kiah, Rafiziana M. Kasmani, Norazana Ibrahim, Roshafima R. Ali, Aziatul N.Sadikin

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An experimental study has been done to investigate the flame acceleration in a closed pipe. A horizontal steel pipe, 2m long and 0.1 m in diameter (L/D of 20), was used in this work. For tests with 90 degree bends, the bend had a radius of 0.1 m and thus, the pipe was lengthened 1 m (based on the centreline length of the segment). Ignition was affected one end of the vessel while the other end was closed. Only stoichiometric concentration (Ф, = 1.0) of natural gas/air mixtures will be reported in this paper. It was demonstrated that bend pipe configuration gave three times higher in maximum over-pressure (5.5 bars) compared to straight pipe (2.0 bars). From the results, the highest flame speed of 63 m s-1 was observed in a gas explosion with bent pipe, greater by a factor of ~3 as compared with straight pipe (23 m s-1). This occurs because bending acts similar to an obstacle, in which this mechanism can induce more turbulence, initiating combustion in an unburned pocket at the corner region and causing a high mass burning rate which increases the flame speed.

Keywords: bending, gas explosion, bending, flame acceleration, over-pressure

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Authors: Ashwini Bhosale, Yogesh Patil

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Urban areas are extremely complicated environmental settings, where health and well-being of an individual and population are governed by a large number of bio-physical, socio-economical, and inclusive aspects. Although poverty and slums are the prime issues under UN-HABITAT agenda of environmental sustainability, slums, the inevitable part of urban environment, have not accounted for inclusive city planning. Developing nations, where about 60 % of world slum population resides, are increasingly under pressure to uplift the urban poor, particularly slum dwellers. From a point of advantage, these new slum redevelopment projects have succeeded in providing legitimized and more permanent and stable shelter for the low income people, as well as individualized sanitation and water supply. However, they unfortunately follow the “one type fits all" approach and exhibit no response to the climatic design needs on Mumbai. The thesis focuses on the study of environmental perspectives in the context of Daylight, natural ventilation and social aspects in the design process of Slum-Rehabilitation schemes (SRS) – case of Mumbai. It attempts to investigate into Indian approaches about SRS and concludes upon strategies to be incorporated in SRS to improve the overall SRS environment. The main objectives of this work have been to identify and study the spatial configuration and possibilities of daylight and natural ventilation in Slum Rehabilitated buildings. The performance of the proposed method was evaluated by comparison with the daylight luminance simulated by lighting software, namely ECOTECT, and with measurements under real skies whereas for the ventilation study purpose, software named FLOW DESIGN was used.

Keywords: urban environment, slum-rehabilitation, daylight, natural-ventilation, architectural consequences

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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: Gül Fatma Türker, Hatice Akman

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Portable muscle stimulators for real-time applications has first introduced by Liberson in 1961. Now these systems has been advanced. In this study, FES (Functional Electrical Stimulator) and NMES (Neuromuscular Electrostimulator) systems are analyzed through their hardware and their quality of life improvements for foot drop patients. FES and NMES systems are used for people whose leg muscles and leg neural connections are healty but not able to walk properly because of their injured central nervous system like spinal cord injuries. These systems are used to stimulate neurons or muscles by getting information from other movements and programming these stimulations to get natural walk and it is accepted as a rehabilitation method for the correction of drop foot. This systems support person to approach natural form of walking. Foot drop is characterized by steppage gait. It is a gait abnormality. This systems helps to person for plantar and dorse reflection movements which are hard to done for foot drop patients.

Keywords: FES, foot drop, NMES, stimulator

Procedia PDF Downloads 388

Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

Procedia PDF Downloads 281

Authors: N. S. B. Ambarini, Tito Sofyan, Edra Satmaidi

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Coastal and marine are two potential natural resource one of the pillars of the national economy. The Indonesian archipelago has marine and coastal which is quite spacious. Various important natural resources such as fisheries, mining and so on are in coastal areas and the sea, so that this region is a unique area with a variety of interests to exploit it. Therefore, to preserve a sustainable manner need good management and comprehensive. To the national and local level legal regulations have been published relating to the management of coastal and marine areas. However, in practice it has not been able to function optimally. Substantially has not touched the problems of the region, especially concerning the interests of local communities (local). This study is a legal non-doctrinal approach to socio-legal studies. Based on the results of research in some coastal and marine areas in Bengkulu province - Indonesia, there is a fact that the system of customary law and local wisdom began to weaken implementation. Therefore harmonization needs to be done in implementing laws and regulations that apply to the values of indigenous and local knowledge that exists in the community.

Keywords: coastal and marine, harmonization, law, local

Procedia PDF Downloads 347

Authors: U. Pruthviraj, Praveen Kumar R. A. K. Athul, K. V. Gangadharan, S. Rao Shrikantha

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An open source based autonomous unmanned marine surface vehicle (UMSV) is developed for some of the marine applications such as pollution control, environmental monitoring and thermal imaging. A double rotomoulded hull boat is deployed which is rugged, tough, quick to deploy and moves faster. It is suitable for environmental monitoring, and it is designed for easy maintenance. A 2HP electric outboard marine motor is used which is powered by a lithium-ion battery and can also be charged from a solar charger. All connections are completely waterproof to IP67 ratings. In full throttle speed, the marine motor is capable of up to 7 kmph. The motor is integrated with an open source based controller using cortex M4F for adjusting the direction of the motor. This UMSV can be operated by three modes: semi-autonomous, manual and fully automated. One of the channels of a 2.4GHz radio link 8 channel transmitter is used for toggling between different modes of the USMV. In this electric outboard marine motor an on board GPS system has been fitted to find the range and GPS positioning. The entire system can be assembled in the field in less than 10 minutes. A Flir Lepton thermal camera core, is integrated with a 64-bit quad-core Linux based open source processor, facilitating real-time capturing of thermal images and the results are stored in a micro SD card which is a data storage device for the system. The thermal camera is interfaced to an open source processor through SPI protocol. These thermal images are used for finding oil spills and to look for people who are drowning at low visibility during the night time. A Real Time clock (RTC) module is attached with the battery to provide the date and time of thermal images captured. For the live video feed, a 900MHz long range video transmitter and receiver is setup by which from a higher power output a longer range of 40miles has been achieved. A Multi-parameter probe is used to measure the following parameters: conductivity, salinity, resistivity, density, dissolved oxygen content, ORP (Oxidation-Reduction Potential), pH level, temperature, water level and pressure (absolute).The maximum pressure it can withstand 160 psi, up to 100m. This work represents a field demonstration of an open source based autonomous navigation system for a marine surface vehicle.

Keywords: open source, autonomous navigation, environmental monitoring, UMSV, outboard motor, multi-parameter probe

Procedia PDF Downloads 241

Authors: D. Kurt, İ. F. Barut, Z. Ü. Yümün, E. Kam

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After development of the industrial revolution, industrial plants and settlements have spread widely on the sea coasts. This concentration also brings environmental pollution in the sea. This study focuses on the Gulf of İzmir where is located in West of Turkey and it is a fascinating natural gulf of the Eastern Aegean Sea. Investigating marine current sediment is extremely important to detect pollution. Natural radionuclides’ pollution of the marine environment which is also known as a significant environmental anxiety. Ground drilling cores (the depth of each sediment is variant) were collected from the Gulf of İzmir’s four different locations which were Karşıyaka, İnciraltı, Çeşmealtı and Bayraklı. These sediment cores were put in preserving bags with weight around 1 kg, and they were dried at room temperature in a week for moisture removal. Then, they were sieved with 1 mm sieve holes, and finally these powdered samples were relocation to polyethylene Marinelli beakers of 100 ml versions. Each prepared sediment was waited to reach radioactive equilibrium between uranium and thorium for 40 days. Gamma spectrometry measurements were settled using a HPG (High- Purity Germanium) semiconductor detector. Semiconductor detectors are very good at separating power of the energy, they are easily able to differentiate peaks that are pretty close to each other. That is why, gamma spectroscopy’s usage is common for the determination of the activities of U - 238, Th - 232, Ra - 226, Cr - 137 and K - 40 in Bq kg⁻¹. In this study, the results display that the average concentrations of activities’ values are in respectively; 2.2 ± 1.5 Bq/ kg⁻¹, 0.98 ± 0.02 Bq/ kg⁻¹, 8 ± 0.96 Bq/ kg⁻¹, 0.93 ± 0.14 Bq/ kg⁻¹, and 76.05 ± 0.93 Bq/ kg⁻¹. The outcomes of the study are able to be used as a criterion for forthcoming research and the obtained data would be pragmatic for radiological mapping of the precise areas.

Keywords: gamma, Gulf of İzmir (Eastern Aegean Sea-Turkey), natural radionuclides, pollution

Procedia PDF Downloads 258

Authors: Esra Alhamal

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Islamic architecture is known for the ornamental patterns that cover the architectural surfaces: floors, walls, and ceilings. This quality in Islamic buildings has long impressed other civilisation, and it is a visual language that exists across the Islamic lands. Ornamentation is divided into three types: geometry, biomorphs, and Arabic calligraphy. The focus of this study is the biomorphic ornaments. This paper will aim to define and characterise biomorphic patterns and trace their development from the 7th to the 18th centuries. Although the time period is seemingly long, the biomorphic patterns and their motifs have been consistent and supported by a geometric system underlying the free flowing, symmetrical motifs. The methodology of this paper consists of analysing and comparing biomorphic patterns from each Islamic period using rules of geometry and symmetry. The study is concluded with a table showcasing the main motifs and how they developed under each Islamic dynasty. This research is a documentation of the biomorphic language and having this record will help contemporary designers employ biomorphic ornaments thoughtfully.

Keywords: architectural surface, biomorphic patterns, Islamic patterns, Islamic ornamentation

Procedia PDF Downloads 151

Authors: Alma Mendoza-Ponce, Rogelio Corona-Núñez, Florian Kraxner

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Mexico is a megadiverse country and it has nearly halved its natural vegetation in the last century due to agricultural and livestock expansion. Impacts of land use cover change and climate change are unevenly distributed and spatial prioritization to minimize the affectations on biodiversity is crucial. Global and national efforts for prioritizing biodiversity conservation show that ~33% to 45% of Mexico should be protected. The width of these targets makes difficult to lead resources. We use a framework based on vulnerability and irreplaceability to prioritize conservation efforts in Mexico. Vulnerability considered exposure, sensitivity and adaptive capacity under two scenarios (business as usual, BAU based, on the SSP2 and RCP 4.5 and a Green scenario, based on the SSP1 and the RCP 2.6). Exposure to land use is the magnitude of change from natural vegetation to anthropogenic covers while exposure to climate change is the difference between current and future values for both scenarios. Sensitivity was considered as the number of endemic species of terrestrial vertebrates which are critically endangered and endangered. Adaptive capacity is used as the ration between the percentage of converted area (natural to anthropogenic) and the percentage of protected area at municipality level. The results suggest that by 2050, between 11.6 and 13.9% of Mexico show vulnerability ≥ 50%, and by 2070, between 12.0 and 14.8%, in the Green and BAU scenario, respectively. From an ecosystem perspective cloud forests, followed by tropical dry forests, natural grasslands and temperate forests will be the most vulnerable (≥ 50%). Amphibians are the most threatened vertebrates; 62% of the endemic amphibians are critically endangered or endangered while 39%, 12% and 9% of the mammals, birds, and reptiles, respectively. However, the distribution of these amphibians counts for only 3.3% of the country, while mammals, birds, and reptiles in these categories represent 10%, 16% and 29% of Mexico. There are 5 municipalities out of the 2,457 that Mexico has that represent 31% of the most vulnerable areas (70%).These municipalities account for 0.05% of Mexico. This multiscale approach can be used to address resources to conservation targets as ecosystems, municipalities or species considering land use cover change, climate change and biodiversity uniqueness.

Keywords: biodiversity, climate change, land use change, Mexico, vulnerability

Procedia PDF Downloads 168

Authors: Drissi Mokhtaria, Chouaih Abdelkader, Fodil Hamzaoui

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Our work is about a comparison of experimental and theoretical results of the electron charge density distribution and the electrostatic potential around the M-Nitrophenol Molecule (m-NPH) kwon for its interesting physical characteristics. The molecular experimental results have been obtained from a high-resolution X-ray diffraction study. Theoretical investigations were performed under the Gaussian program using the Density Functional Theory at B3LYP level of theory at 6-31G*. The multipolar model of Hansen and Coppens was used for the experimental electron charge density distribution around the molecule, while we used the DFT methods for the theoretical calculations. The electron charge density obtained in both methods allowed us to find out the different molecular properties such us the electrostatic potential and the dipole moment which were finally subject to a comparison leading to an outcome of a good matching results obtained in both methods.

Keywords: electron charge density, m-nitrophenol, nonlinear optical compound, electrostatic potential, optimized geometric

Procedia PDF Downloads 268

Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

Procedia PDF Downloads 74

Authors: Ethan James

Abstract:

Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 181

Authors: Saleh Nabiyev

Abstract:

Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

Procedia PDF Downloads 32