Search results for: cloud computing (MCC)

Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Kuniyoshi Abe

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Bi-conjugate gradient (Bi-CG) is a well-known method for solving linear equations Ax = b, for x, where A is a given n-by-n matrix, and b is a given n-vector. Typically, the dimension of the linear equation is high and the matrix is sparse. A number of hybrid Bi-CG methods such as conjugate gradient squared (CGS), Bi-CG stabilized (Bi-CGSTAB), BiCGStab2, and BiCGstab(l) have been developed to improve the convergence of Bi-CG. Bi-CGSTAB has been most often used for efficiently solving the linear equation, but we have seen the convergence behavior with a long stagnation phase. In such cases, it is important to have Bi-CG coefficients that are as accurate as possible, and the stabilization strategy, which stabilizes the computation of the Bi-CG coefficients, has been proposed. It may avoid stagnation and lead to faster computation. Motivated by a large number of processors in present petascale high-performance computing hardware, the scalability of Krylov subspace methods on parallel computers has recently become increasingly prominent. The main bottleneck for efficient parallelization is the inner products which require a global reduction. The resulting global synchronization phases cause communication overhead on parallel computers. The parallel variants of Krylov subspace methods reducing the number of global communication phases and hiding the communication latency have been proposed. However, the numerical stability, specifically, the convergence speed of the parallel variants of Bi-CGSTAB may become worse than that of the standard Bi-CGSTAB. In this paper, therefore, we compare the convergence speed between the standard Bi-CGSTAB and the parallel variants by numerical experiments and show that the convergence speed of the standard Bi-CGSTAB is faster than the parallel variants. Moreover, we propose the stabilization strategy for the parallel variants.

Keywords: bi-conjugate gradient stabilized method, convergence speed, Krylov subspace methods, linear equations, parallel variant

Procedia PDF Downloads 167

Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

Procedia PDF Downloads 112

Authors: Azadeh Jafari, Robert G. Owens

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In this study, a geometrical multiscale approach which means coupling together the 2-D Navier-Stokes equations, constitutive equations and 0-D lumped parameter models is investigated. A multiscale approach, suggest a natural way of coupling detailed local models (in the flow domain) with coarser models able to describe the dynamics over a large part or even the whole cardiovascular system at acceptable computational cost. In this study we introduce a new velocity correction scheme to decouple the velocity computation from the pressure one. To evaluate the capability of our new scheme, a comparison between the results obtained with Neumann outflow boundary conditions on the velocity and Dirichlet outflow boundary conditions on the pressure and those obtained using coupling with the lumped parameter model has been performed. Comprehensive studies have been done based on the sensitivity of numerical scheme to the initial conditions, elasticity and number of spectral modes. Improvement of the computational algorithm with stable convergence has been demonstrated for at least moderate Weissenberg number. We comment on mathematical properties of the reduced model, its limitations in yielding realistic and accurate numerical simulations, and its contribution to a better understanding of microvascular blood flow. We discuss the sophistication and reliability of multiscale models for computing correct boundary conditions at the outflow boundaries of a section of the cardiovascular system of interest. In this respect the geometrical multiscale approach can be regarded as a new method for solving a class of biofluids problems, whose application goes significantly beyond the one addressed in this work.

Keywords: geometrical multiscale models, haemorheology model, coupled 2-D navier-stokes 0-D lumped parameter modeling, computational fluid dynamics

Procedia PDF Downloads 365

Authors: Khalid Omari, Rene Chenier, Enrique Blondel, Ryan Ahola

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Northern Canadian coasts have vulnerable and very dynamic intertidal zones with very high tides occurring in several areas. The impact of climate change presents challenges not only for maintaining this biodiversity but also for navigation safety adaptation due to the high sediment mobility in these coastal areas. Thus, frequent mapping of shorelines and intertidal changes is of high importance. To help in quantifying the changes in these fragile ecosystems, remote sensing provides practical monitoring tools at local and regional scales. Traditional methods based on high-resolution optical sensors are often used to map intertidal areas by benefiting of the spectral response contrast of intertidal classes in visible, near and mid-infrared bands. Tidal areas are highly reflective in visible bands mainly because of the presence of fine sand deposits. However, getting a cloud-free optical data that coincide with low tides in intertidal zones in northern regions is very difficult. Alternatively, the all-weather capability and daylight-independence of the microwave remote sensing using synthetic aperture radar (SAR) can offer valuable geophysical parameters with a high frequency revisit over intertidal zones. Multi-polarization SAR parameters have been used successfully in mapping intertidal zones using incoherence target decomposition. Moreover, the crustal displacements caused by ocean tide loading may reach several centimeters that can be detected and quantified across differential interferometric synthetic aperture radar (DInSAR). Soil moisture change has a significant impact on both the coherence and the backscatter. For instance, increases in the backscatter intensity associated with low coherence is an indicator for abrupt surface changes. In this research, we present primary results obtained following our investigation of the potential of the fully polarimetric Radarsat-2 data for mapping an inter-tidal zone located on Tasiujaq on the south-west shore of Ungava Bay, Quebec. Using the repeat pass cycle of Radarsat-2, multiple seasonal fine quad (FQ14W) images are acquired over the site between 2016 and 2018. Only 8 images corresponding to low tide conditions are selected and used to build an interferometric stack of data. The observed displacements along the line of sight generated using HH and VV polarization are compared with the changes noticed using the Freeman Durden polarimetric decomposition and Touzi degree of polarization extrema. Results show the consistency of both approaches in their ability to monitor the changes in intertidal zones.

Keywords: SAR, degree of polarization, DInSAR, Freeman-Durden, polarimetry, Radarsat-2

Procedia PDF Downloads 143

Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

Procedia PDF Downloads 387

Authors: Simon Caba, Raja Abou Ackl, Svend Rasmussen, Nicholas E. Pedersen

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It is a challenge to directly monitor cavitation in a pump application during operation because of a lack of visual access to validate the presence of cavitation and its form of appearance. In this work, experimental investigations are carried out in an inline single-stage centrifugal pump with optical access. Hence, it gives the opportunity to enhance the value of CFD tools and standard cavitation measurements. Experiments are conducted using two impellers running in the same volute at 3000 rpm and the same flow rate. One of the impellers used is optimized for lower NPSH₃% by its blade design, whereas the other one is manufactured using a standard casting method. The cavitation is detected by pump performance measurements, vibration measurements and high-speed image recordings. The head drop and the pump casing vibration caused by cavitation are correlated with the visual appearance of the cavitation. The vibration data is recorded in an axial direction of the impeller using accelerometers recording at a sample rate of 131 kHz. The vibration frequency domain data (up to 20 kHz) and the time domain data are analyzed as well as the root mean square values. The high-speed recordings, focusing on the impeller suction side, are taken at 10,240 fps to provide insight into the flow patterns and the cavitation behavior in the rotating impeller. The videos are synchronized with the vibration time signals by a trigger signal. A clear correlation between cloud collapses and abrupt peaks in the vibration signal can be observed. The vibration peaks clearly indicate cavitation, especially at higher NPSHA values where the hydraulic performance is not affected. It is also observed that below a certain NPSHA value, the cavitation started in the inlet bend of the pump. Above this value, cavitation occurs exclusively on the impeller blades. The impeller optimized for NPSH₃% does show a lower NPSH₃% than the standard impeller, but the head drop starts at a higher NPSHA value and is more gradual. Instabilities in the head drop curve of the optimized impeller were observed in addition to a higher vibration level. Furthermore, the cavitation clouds on the suction side appear more unsteady when using the optimized impeller. The shape and location of the cavitation are compared to 3D fluid flow simulations. The simulation results are in good agreement with the experimental investigations. In conclusion, these investigations attempt to give a more holistic view on the appearance of cavitation by comparing the head drop, vibration spectral data, vibration time signals, image recordings and simulation results. Data indicates that a criterion for cavitation detection could be derived from the vibration time-domain measurements, which requires further investigation. Usually, spectral data is used to analyze cavitation, but these investigations indicate that the time domain could be more appropriate for some applications.

Keywords: cavitation, centrifugal pump, head drop, high-speed image recordings, pump vibration

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Authors: Zulkifli Zainal Abidin, Ahmad Shahril Mohd Ghani

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Agent-based systems technology has been addressed as a new paradigm for conceptualizing, designing, and implementing software systems. Agents are sophisticated systems that act autonomously across open and distributed environments in solving problems. Nevertheless, it is impractical to rely on a single agent to do all computing processes in solving complex problems. An increasing number of applications lately require multiple agents to work together. A multi-agent system (MAS) is a loosely coupled network of agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver. However, the network of MAS still requires a main system to govern or oversees the operation of the agents in order to achieve a unified goal. We had developed a fleet management system (FMS) in order to manage the fleet of agents, plan route for the agents, perform real-time data processing and analysis, and issue sets of general and specific instructions to the agents. This FMS should be able to perform real-time data processing, communicate with the autonomous surface vehicle (ASV) agents and generate bathymetric map according to the data received from each ASV unit. The first algorithm is developed to communicate with the ASV via radio communication using standard National Marine Electronics Association (NMEA) protocol sentences. Next, the second algorithm will take care of the path planning, formation and pattern generation is tested using various sample data. Lastly, the bathymetry map generation algorithm will make use of data collected by the agents to create bathymetry map in real-time. The outcome of this research is expected can be applied on various other multi-agent systems.

Keywords: autonomous surface vehicle, fleet management system, multi agent system, bathymetry

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Authors: Saif Obaid Alkaabi, Nabil Ayad

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Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.

Keywords: e-government, m-government, system dependability, system security, trust

Procedia PDF Downloads 384

Authors: Jonathan Martino, Kristof Harri

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In some cases, the increase in computing resources makes simulation methods more affordable. The increase in processing speed also allows real time analysis or even more rapid tests analysis offering a real tool for test prediction and design process optimization. Vibration tests are no exception to this trend. The so called ‘Virtual Vibration Testing’ offers solution among others to study the influence of specific loads, to better anticipate the boundary conditions between the exciter and the structure under test, to study the influence of small changes in the structure under test, etc. This article will first present a virtual vibration test modeling with a main focus on the shaker model and will afterwards present the experimental parameters determination. The classical way of modeling a shaker is to consider the shaker as a simple mechanical structure augmented by an electrical circuit that makes the shaker move. The shaker is modeled as a two or three degrees of freedom lumped parameters model while the electrical circuit takes the coil impedance and the dynamic back-electromagnetic force into account. The establishment of the equations of this model, describing the dynamics of the shaker, is presented in this article and is strongly related to the internal physical quantities of the shaker. Those quantities will be reduced into global parameters which will be estimated through experiments. Different experiments will be carried out in order to design an easy and practical method for the identification of the shaker parameters leading to a fully functional shaker model. An experimental modal analysis will also be carried out to extract the modal parameters of the shaker and to combine them with the electrical measurements. Finally, this article will conclude with an experimental validation of the model.

Keywords: lumped parameters model, shaker modeling, shaker parameters, state-space, virtual vibration

Procedia PDF Downloads 273

Authors: Radek Richtr, Petr Pauš

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Social media nowadays connects people more tightly and intensively than ever, but simultaneously, some sort of social distance, incomprehension, lost of social integrity appears. People can be strongly connected to the person on the other side of the world but unaware of neighbours in the same district or street. The Stoa is a type of application from the ”serious games” genre- it is research augmented reality experiment masked as a gaming environment. In the Stoa environment, the player can plant and grow virtual (organic) structure, a Pillar, that represent the whole suburb. Everybody has their own idea of what is an acceptable, admirable or harmful visual intervention in the area they live in; the purpose of this research experiment is to find and/or define residents shared subconscious spirit, genius loci of the Pillars vicinity, where residents live in. The appearance and evolution of Stoa’s Pillars reflect the real world as perceived by not only the creator but also by other residents/players, who, with their actions, refine the environment. Squares, parks, patios and streets get their living avatar depictions; investors and urban planners obtain information on the occurrence and level of motivation for reshaping the public space. As the project is in product conceptual design phase, the function is one of its most important factors. Function-based modelling makes design problem modular and structured and thus decompose it into sub-functions or function-cells. Paper discuss the current conceptual model for Stoa project, the using of different organic structure textures and models, user interface design, UX study and project’s developing to the final state.

Keywords: augmented reality, urban computing, interaction design, mixed reality, social engineering

Procedia PDF Downloads 233

Authors: Suangsuda Subjaroen, Chutikarn Sriviboon, Rosjana Chandhasa

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This research aims to examine the graduates' overall satisfaction and influential factors that affect the image of Suan Sunandha Rajabhat University, according to the graduates' viewpoints on the graduation rehearsal day. In accordance with the graduates' perceptions, the study is related to the levels of graduates' satisfaction, their perceived quality, perceived value, and the image of Suan Sunandha Rajabhat University. The sample group in this study involved 1,129 graduates of Suan Sunandha Rajabhat University who attended on 2019 graduation rehearsal day. A questionnaire was used as an instrument in order to collect data. By the use of computing software, the statistics used for data analysis were various, ranging from frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and Multiple Regression Analysis. The majority of participants were graduates with a bachelor's degree, followed by masters graduates and PhD graduates, respectively. Among the participants, most of them graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. Overall, the graduates were satisfied with the graduation rehearsal day, and each aspect was rated at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation rehearsal personnel and staff, venue, and facilities. Referring to graduates' perceptions, the perceived quality was rated at a very good level, the perceived value was at a good level, whereas the image of Suan Sunandha Rajabhat University was perceived at a good level, respectively. There were differences in satisfaction levels among graduates with a bachelor's degree, graduates with a master's degree and a doctoral degree with statistical significance at the level of 0.05. There was a statistical significance at the level of 0.05 in perceived quality and perceived value affecting the image of Suan Sunandha Rajabhat University. The image of Suan Sunandha Rajabhat University influenced graduates' satisfaction level with statistical significance at the level of 0.01.

Keywords: university image, perceived quality, perceived value, intention to study higher education, intention to recommend the university to others

Procedia PDF Downloads 116

Authors: Waraphorn Sribuakaew, Chutikarn Sriviboon, Rosjana Chandhasa

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The purpose of this research is to study the satisfaction level of graduates and factors that affect the image of Suan Sunandha Rajabhat University based on the perceptions of graduates on the graduation ceremony day. By studying the satisfaction of graduates, the image of Suan Sunandha Rajabhat University according to the graduates' perceptions and the loyalty to the university (in the aspects of intention to continue studying at a higher level, intention to recommend the university to a friend), the sample group used in this study was 1,000 graduates of Suan Sunandha Rajabhat University who participated on the 2019 graduation ceremony day. A questionnaire was utilized as a tool for data collection. By the use of computing software, the statistics used for data analysis were frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and multiple regression analysis. Most of the respondents were graduates with a bachelor's degree, followed by graduates with a master's degree and PhD graduates, respectively. Major participants graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. The graduates were satisfied on the ceremony day as a whole and rated each aspect at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation ceremony personnel and staff, venue, and facilities. On the perception of the graduates, the image of Suan Sunandha Rajabhat University was at a good level, while loyalty to the university was at a very high level. The intention of recommendation to others was at the highest level, followed by the intention to pursue further education at a very high level. The graduates graduating from different faculties have different levels of satisfaction on the graduation day with statistical significance at the level of 0.05. The image of Suan Sunandha Rajabhat University affected the satisfaction of graduates with statistical significance at the level of 0.01. The satisfactory level of graduates on the graduation ceremony day influenced the level of loyalty to the university with statistical significance at the level of 0.05.

Keywords: university image, loyalty to the university, intention to study higher education, intention to recommend the university to others, graduates' satisfaction

Procedia PDF Downloads 137

Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

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Authors: Helen L. Hein, Joachim Schwarte

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As a pillar of sustainable development, ecology has become an important milestone in research community, especially due to global challenges like climate change. The ecological performance of products can be scientifically conducted with life cycle assessments. In the construction sector, significant amounts of CO₂ emissions are assigned to the energy used for building heating purposes. Therefore, sustainable construction materials for insulating purposes are substantial, whereby aerogels have been explored intensively in the last years due to their low thermal conductivity. Therefore, the WALL-ACE project aims to develop an aerogel-based thermal insulating plaster that would achieve minor thermal conductivities. But as in the early stage of development phases, a lot of information is still missing or not yet accessible, the ecological performance of innovative products bases increasingly on uncertain data that can lead to significant deviations in the results. To be able to predict realistically how meaningful the results are and how viable the developed products may be with regard to their corresponding respective market, these deviations however have to be considered. Therefore, a classification method is presented in this study, which may allow comparing the ecological performance of modern products with already established and competitive materials. In order to achieve this, an alternative calculation method was used that allows computing with lower and upper bounds to consider all possible values without precise data. The life cycle analysis of the considered products was conducted with an interval arithmetic based calculation method. The results lead to the conclusion that the interval solutions describing the possible environmental impacts are so wide that the result usability is limited. Nevertheless, a further optimization in reducing environmental impacts of aerogels seems to be needed to become more competitive in the future.

Keywords: aerogel-based, insulating material, early development phase, interval arithmetic

Procedia PDF Downloads 146

Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

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Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

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Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 179

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

Procedia PDF Downloads 149

Authors: Akshay Patil

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Objective: Mediation analysis identifies causal pathways by testing the relationships between the NCR, the OS, and an intermediate variable that mediates the relationship between the Nimotuzumab-cisplatin-radiation (NCR) and OS. Introduction: In randomized controlled trials, the primary interest is in the mechanisms by which an intervention exerts its effects on the outcomes. Clinicians are often interested in how the intervention works (or why it does not work) through hypothesized causal mechanisms. In this work, we highlight the value of understanding causal mechanisms in randomized trial by applying causal mediation analysis in a randomized trial in oncology. Methods: Data was obtained from a phase III randomized trial (Subgroup of HPVNOCP). NCR is reported to significantly improve the OS of patients locally advanced head and neck cancer patients undergoing definitive chemoradiation. Here, based on trial data, the mediating effect of NCR on patient overall survival was systematically quantified through progression-free survival(PFS), disease free survival (DFS), Loco-regional failure (LRF), and the disease control rate (DCR), Overall response rate (ORR). Effects of potential mediators on the HR for OS with NCR versus cisplatin-radiation (CR) were analyzed by Cox regression models. Statistical analyses were performed using R software Version 3.6.3 (The R Foundation for Statistical Computing) Results: Effects of potential mediator PFS was an association between NCR treatment and OS, with an indirect-effect (IE) 0.76(0.62 – 0.95), which mediated 60.69% of the treatment effect. Taking into account baseline confounders, the overall adjusted hazard ratio of death was 0.64 (95% CI: 0.43 – 0.96; P=0.03). The DFS was also a significant mediator and had an IE 0.77 (95% CI; 0.62-0.93), 58% mediated). Smaller mediation effects (maximum 27%) were observed for LRF with IE 0.88(0.74 – 1.06). Both DCR and ORR mediated 10% and 15%, respectively, of the effect of NCR vs. CR on the OS with IE 0.65 (95% CI; 0.81 – 1.08) and 0.94(95% CI; 0.79 – 1.04). Conclusion: Our findings suggest that PFS and DFS were the most important mediators of the OS with nimotuzumab to weekly cisplatin-radiation in HPVNOCP.

Keywords: mediation analysis, cancer data, survival, NCR, HPV negative oropharyngeal

Procedia PDF Downloads 149

Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

Procedia PDF Downloads 179

Authors: Vishal V. R. Nandigana, Mohammad Heiranian, Narayana R. Aluru

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Graphene material has found tremendous applications in water desalination, DNA sequencing and energy storage. Multiple nanopores are etched to create opening for water desalination and energy storage applications. The nanopores created are of the order of 3-5 nm allowing multiple ions to transport through the pore. In this paper, we present for the first time, molecular dynamics study of single ion transport, where only one ion passes through the graphene nanopore. The diameter of the graphene nanopore is of the same order as the hydration layers formed around each ion. Analogous to single electron transport resulting from ionic transport is observed for the first time. The current-voltage characteristics of such a device are similar to single electron transport in quantum dots. The current is blocked until a critical voltage, as the ions are trapped inside a hydration shell. The trapped ions have a high energy barrier compared to the applied input electrical voltage, preventing the ion to break free from the hydration shell. This region is called “Coulomb blockade region”. In this region, we observe zero transport of ions inside the nanopore. However, when the electrical voltage is beyond the critical voltage, the ion has sufficient energy to break free from the energy barrier created by the hydration shell to enter into the pore. Thus, the input voltage can control the transport of the ion inside the nanopore. The device therefore acts as a binary storage unit, storing 0 when no ion passes through the pore and storing 1 when a single ion passes through the pore. We therefore postulate that the device can be used for fluidic computing applications in chemistry and biology, mimicking a computer. Furthermore, the trapped ion stores a finite charge in the Coulomb blockade region; hence the device also acts a super capacitor.

Keywords: graphene nanomembrane, single ion transport, Coulomb blockade, nanofluidics

Procedia PDF Downloads 324

Authors: Shanti Swaroop Mokkapati

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The unstruck sound, or the Anahata Nada, holds the key in elevating the consciousness levels of the practitioner. This has been well established by the great saints of the eastern tradition over the past few centuries. This paper intends to explore in-depth the common thread of the practice of Anahata Nada by the musical saints, examining the subtle mention in their compositions as well as demystifying their musical experiences that throw insights into elevated levels of consciousness. Mian Tansen, one of the greatest musicians in the North Indian Hindustani Classical Music tradition and who lived in the 15th century, is said to have brought rain through his singing of Raga Megh Malhar. The South Indian (Carnatic) Musical Saint Tyagaraja, who lived in the 18th Century, composed hundreds of musical pieces full of love for the Supreme Being. Many of these compositions unravel the secrets of Anahata Nada, the chakras in the human body that hold key to these practices, and the visions of elevated levels of consciousness that Saint Tyagaraja himself experienced through these practices. The spiritual practitioners of the Radhasoami Faith (Religion of Saints) in Dayalbagh, India, have adopted a practice called Surat Shabda Yoga (Meditational practices that unite the all-pervasive sound current with the spirit current and elevate levels of consciousness). The practitioners of this Yogic method submit that they have been able to hear mystic words including Om, Racing, Soham, Sat, and Radhasoami, along with instrumental sounds that accompany these mystic words in the form of a crescendo. These prolific experiences of elevated consciousness of musical saints are numerous, and this paper intends to explore more significant ones from many centuries in the past till the present day, where elevated consciousness levels of practitioners are being scientifically measured and analyzed using quantum computing.

Keywords: Anahata Nada, Nada Yoga, Tyagaraja, Radhasoami

Procedia PDF Downloads 180

Authors: King Kumire, Amos Kubeka

Abstract:

The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: machine-learning, habitability, exoplanets, supercomputing

Procedia PDF Downloads 93

Authors: King Kumire, Amos Kubeka

Abstract:

The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far, has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: exoplanets, habitability, machine-learning, supercomputing

Procedia PDF Downloads 120

Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

Procedia PDF Downloads 344

Authors: Sisay Tiroro Salato

Abstract:

Background: Ethiopia has been implementing the maternal death surveillance and response system to provide real-time actionable information, including causes of death and contributing factors. Analysis of maternal mortality surveillance data was conducted to identify the causes and underlying factors in Addis Ababa, Ethiopia. Methods: We carried out a retrospective surveillance data analysis of 324 maternal deaths reported in Addis Ababa, Ethiopia, from 2017 to 2021. The data were extracted from the national maternal death surveillance and response database, including information from case investigation, verbal autopsy, and facility extraction forms. The data were analyzed by computing frequency and presented in numbers, proportions, and ratios. Results: Of 324 maternal deaths, 92% died in the health facilities, 6.2% in transit, and 1.5% at home. The mean age at death was 28 years, ranging from 17 to 45. The maternal mortality ratio per 100,000 live births was 77for the five years, ranging from 126 in 2017 to 21 in 2021. The direct and indirect causes of death were responsible for 87% and 13%, respectively. The direct causes included obstetric haemorrhage, hypertensive disorders in pregnancy, puerperal sepsis, embolism, obstructed labour, and abortion. The third delay (delay in receiving care after reaching health facilities) accounted for 57% of deaths, while the first delay (delay in deciding to seek health care) and the second delay (delay in reaching health facilities) and accounted for 34% and 24%, respectively. Late arrival to the referral facility, delayed management after admission, andnon-recognition of danger signs were underlying factors. Conclusion: Over 86% of maternal deaths were attributed by avoidable direct causes. The majority of women do try to reach health services when an emergency occurs, but the third delays present a major problem. Improving the quality of care at the healthcare facility level will help to reduce maternal death.

Keywords: maternal death, surveillance, delays, factors

Procedia PDF Downloads 116

Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

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Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor

Procedia PDF Downloads 224

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

Abstract:

Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

Procedia PDF Downloads 140