Search results for: global navigation satellite network

Authors: Tejaswi Agarwal, Amritansh Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Shahul Hamid Khan, S. Santhosh, Abhinav Kumar Sharma

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Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Bi-objective mathematical models for total cost and total emission for the entire forward supply chain are considered. Here five different problems are considered by varying the number of suppliers, manufacturers, and environmental levels, for illustrating the taken mathematical model. GA, and Random search are used for finding the optimal solution. The input parameters of the optimal solution are used to find the tradeoff between the initial investment by the industry and the long term benefit of the environment.

Keywords: closed loop supply chain, genetic algorithm, random search, green supply chain

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Authors: Kimaya Subhash Gaikwad, S. B. Waykar

Abstract:

The mobile ad-hoc network (MANET) is collection of various types of nodes. In MANET various protocols are used for communication. In OLSR protocol, a node is selected as multipoint relay (MPR) node which broadcast the messages. As the MANET is open kind of network any malicious node can easily enter into the network and affect the performance of the network. The performance of network mainly depends on the components which are taking part into the communication. If the proper nodes are not selected for the communication then the probability of network being attacked is more. Therefore, it is important to select the more reliable and secure components in the network. MANET does not have any filtering so that only selected nodes can be used for communication. The openness of the MANET makes it easier to attack the communication. The most of the attack are on the Quality of service (QoS) of the network. This paper gives the overview of the various attacks that are possible on OLSR protocol and some solutions. The papers focus mainly on the OLSR protocol.

Keywords: communication, MANET, OLSR, QoS

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Authors: Maath M. Musleh

Abstract:

This research aims to study recent trends in the Palestinian feminist movement through the case study of Tal3at. The study uses social network analysis as its primary method to analyze Twitter data. It attempts to interpret results through the lens of network theories and Parson’s AGIL paradigm. The study reveals major structural weaknesses in the Tal3at network. Our findings suggest that the movement will decline soon as sentiments of alienation amongst Palestinian women increases. These findings were validated by a couple of central actors in the network. This study contributes an SNA approach to the understanding of the understudied Palestinian feminism.

Keywords: feminism, Palestine, social network analysis, Tal3at

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Authors: Sumaira Zafar, Arjumand Zaidi

Abstract:

During past few years, several floods have adversely affected the areas along lower Indus River. Besides other climate related anomalies, rapidly increasing urbanization and blockage of natural drains due to siltation or encroachments are two other critical causes that may be responsible for these disasters. Due to flat topography of river Indus plains and blockage of natural waterways, drainage of storm water takes time adversely affecting the crop health and soil properties of the area. Government of Sindh is taking a keen interest in revival of natural drainage network in the province and has initiated this work under Sindh Irrigation and Drainage Authority. In this paper, geospatial techniques are used to analyze landuse/land-cover changes of Larkana district over the past three decades (1980-present) and their impact on natural drainage system. Satellite derived Digital Elevation Model (DEM) and topographic sheets (recent and 1950) are used to delineate natural drainage pattern of the district. The urban landuse map developed in this study is further overlaid on drainage line layer to identify the critical areas where the natural floodwater flows are being inhibited by urbanization. Rainfall and flow data are utilized to identify areas of heavy flow, whereas, satellite data including Landsat 7 and Google Earth are used to map previous floods extent and landuse/cover of the study area. Alternatives to natural drainage systems are also suggested wherever possible. The output maps of natural drainage pattern can be used to develop a decision support system for urban planners, Sindh development authorities and flood mitigation and management agencies.

Keywords: geospatial techniques, satellite data, natural drainage, flood, urbanization

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Authors: Abdulqader Rasool Feqi Mohammed, Ergun Erçelebi̇

Abstract:

A large number of hospitals from developed countries are adopting hospital information system to bring efficiency in hospital information system. The purpose of this project is to research on new network security techniques in order to enhance the current network security structure of save a hospital information system (HIS). This is very important because, it will avoid the system from suffering any attack. Security architecture was optimized but there are need to keep researching on best means to protect the network from future attacks. In this final project research, security techniques were uncovered to produce best network security results when implemented in an integrated framework.

Keywords: hospital information system, HIS, network security techniques, internet protocol, IP, network

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Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Affan Ahmed

Abstract:

This research investigates the impact of the geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies.

Keywords: geomagnetic storms, ionospheric disturbances, space weather effects, magnetosphere-ionosphere coupling

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Ghada Moussa, Mamoud Owais

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Transit Route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Keywords: integer programming, transit route design, transportation, urban planning

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Authors: Sidra Shabbir, Ayesha Manzoor, Mehreen Sirshar

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The use of the network communication has imposed serious threats to the security of assets over the network. Network security is getting more prone to active and passive attacks which may result in serious consequences to data integrity, confidentiality and availability. Various cryptographic techniques have been proposed in the past few years to combat with the concerned problem by ensuring quality but in order to have a fully secured network; a framework of new cryptosystem was needed. This paper discusses certain cryptographic techniques which have shown far better improvement in the network security with enhanced quality assurance. The scope of this research paper is to cover the security pitfalls in the current systems and their possible solutions based on the new cryptosystems. The development of new cryptosystem framework has paved a new way to the widespread network communications with enhanced quality in network security.

Keywords: cryptography, network security, encryption, decryption, integrity, confidentiality, security algorithms, elliptic curve cryptography

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Authors: Feng-jie Xie, Jian-hong Yan

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Based on the complex network theory, we construct the air cargo network of the Belt and Road area, analyze its regional distribution and structural characteristics, measure the robustness of the network. The regional distribution results show that Southeast Asia and China have the most prominent development in the air cargo network of the Belt and Road area, Central Asia is the least developed. The structure characteristics found that the air cargo network has obvious small-world characteristics; the degree distribution has single-scale property; it shows a significant rich-club phenomenon simultaneously. The network robustness is measured by two attack strategies of degree and betweenness, but the betweenness of network nodes has a greater impact on network connectivity. And identified 24 key cities that have a large impact on the robustness of the network under the two attack strategies. Based on these results, recommendations are given to maintain the air cargo network connectivity in the Belt and Road area.

Keywords: air cargo, complex network, robustness, structure properties, The Belt and Road

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Authors: Victor Emeli, Akansel Cosgun

Abstract:

This paper explores the navigation among movable obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a rapidly-exploring random tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).

Keywords: motion planning, path planning, push planning, robot navigation

Procedia PDF Downloads 165

Authors: Affan Ahmed

Abstract:

This research investigates the Influence of geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies.

Keywords: geomagnetic storms, ionospheric disturbances, space weather effects, magnetosphere-ionopheric coupling

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Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner

Abstract:

Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Keywords: calculation of risk factor, fuzzy logic, fuzzy programming for ship, safety navigation of ships

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Authors: Jin Xu

Abstract:

5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: Sadaoui Djaouida

Abstract:

In this paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.

Keywords: predictive control, synchronization, satellite attitude, control engineering

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Mary Goitom, Maria Liegghio

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In this paper, we critically explore the ethics of Schools of Social Work from the global North developing courses for programs within the Global South. In it, we discuss our experiences of partnering with the University of Guyana to develop and teach graduate courses in a newly formed Masters of Social Work program. Under the umbrella of our university’s goal for 'internationalization', that is, developing and establishing global and local collaborations for teaching, research and scholarship, we bring into question whether a new form of academic imperialism is occurring under the guise of global citizenship and social justice.

Keywords: academic imperialism, global north and south, internationalization, social work education

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Authors: V. Andal Priyadharshini, Anumalasetty Yashwanth Nath

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Network automation has evolved into a solution that ensures efficiency in all areas. The age-old technique to configure common software-defined networking protocols is inefficient as it requires a box-by-box approach that needs to be repeated often and is prone to manual errors. Network automation assists network administrators in automating and verifying the protocol configuration to ensure consistent configurations. This paper implemented network automation using Python and Ansible to configure different protocols and configurations in the container lab virtual environment. Ansible can help network administrators minimize human mistakes, reduce time consumption, and enable device visibility across the network environment.

Keywords: Python network automation, Ansible configuration, container lab deployment, software-defined networking, networking lab

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Authors: Walid Wahballah, Taher Bazan, Fawzy Eltohamy

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One of the important functions of the satellite attitude control system is to provide the required pointing accuracy and attitude stability for optical remote sensing satellites to achieve good image quality. Although offering noise reduction and increased sensitivity, time delay and integration (TDI) charge coupled devices (CCDs) utilized in high-resolution satellites (HRS) are prone to introduce large amounts of pixel smear due to the instability of the line of sight. During on-orbit imaging, as a result of the Earth’s rotation and the satellite platform instability, the moving direction of the TDI-CCD linear array and the imaging direction of the camera become different. The speed of the image moving on the image plane (focal plane) represents the image motion velocity whereas the angle between the two directions is known as the drift angle (β). The drift angle occurs due to the rotation of the earth around its axis during satellite imaging; affecting the geometric accuracy and, consequently, causing image quality degradation. Therefore, the image motion velocity vector and the drift angle are two important factors used in the assessment of the image quality of TDI-CCD based optical remote sensing satellites. A model for estimating the image motion velocity and the drift angle in HRS is derived. The six satellite attitude control parameters represented in the derived model are the (roll angle φ, pitch angle θ, yaw angle ψ, roll angular velocity φ֗, pitch angular velocity θ֗ and yaw angular velocity ψ֗ ). The influence of these attitude parameters on the image quality is analyzed by establishing a relationship between the image motion velocity vector, drift angle and the six satellite attitude parameters. The influence of the satellite attitude parameters on the image quality is assessed by the presented model in terms of modulation transfer function (MTF) in both cross- and along-track directions. Three different cases representing the effect of pointing accuracy (φ, θ, ψ) bias are considered using four different sets of pointing accuracy typical values, while the satellite attitude stability parameters are ideal. In the same manner, the influence of satellite attitude stability (φ֗, θ֗, ψ֗) on image quality is also analysed for ideal pointing accuracy parameters. The results reveal that cross-track image quality is influenced seriously by the yaw angle bias and the roll angular velocity bias, while along-track image quality is influenced only by the pitch angular velocity bias.

Keywords: high-resolution satellites, pointing accuracy, attitude stability, TDI-CCD, smear, MTF

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Authors: Manuel Meranza-Castillon, Rolando Diaz-Castillo, Adrian Arellano-Delgado, Cesar Cruz-Hernandez, Rosa Martha Lopez-Gutierrez

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In this work, we deal with experimental network synchronization of chaotic nodes with different topologies. Our approach is based on complex system theory, and we use a master-slave configuration to couple the nodes in the networks. In particular, we design and implement electronically complex dynamical networks composed by nine coupled chaotic Chua’s circuits with topologies: in nearest-neighbor, small-world, open ring, star, and global. Also, network synchronization is evaluated according to a particular coupling strength for each topology. This study is important by the possible applications to private transmission of information in a chaotic communication network of multiple users.

Keywords: complex networks, Chua's circuit, experimental synchronization, multiple users

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Authors: S. Benkraouda, Z. Djelloul-Khedda, B. Yagoubi

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we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection.

Keywords: forest fire, forest fire detection, satellite image, normal distribution, theoretical gaussian model, thermal infrared matrix image

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Authors: Satyam Raikwar, Thomas Herlitzius, Jens Fehrmann

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In recent years, the autonomous navigation of orchard and field robots is an emerging technology of the mobile robotics in agriculture. One of the core aspects of autonomous navigation builds upon path planning, which is still a crucial issue. Generally, for simple representation, the path planning for a mobile robot is performed in a two-dimensional space, which creates a path between the start and goal point. This paper presents the automatic path planning approach for robots used in orchards and vineyards using occupancy grid maps with field consideration. The orchards and vineyards are usually structured environment and their topology is assumed to be constant over time; therefore, in this approach, an RGB image of a field is used as a working environment. These images undergone different image processing operations and then discretized into two-dimensional grid matrices. The individual grid or cell of these grid matrices represents the occupancy of the space, whether it is free or occupied. The grid matrix represents the robot workspace for motion and path planning. After the grid matrix is described, a probabilistic roadmap (PRM) path algorithm is used to create the obstacle-free path over these occupancy grids. The path created by this method was successfully verified in the test area. Furthermore, this approach is used in the navigation of the orchard robot.

Keywords: orchard robots, automatic path planning, occupancy grid, probabilistic roadmap

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Authors: Shivangi Somvanshi

Abstract:

Poor crop productivity in salt-affected environment in the country is due to insufficient and untimely canal supply to agricultural land and inefficient field water management practices. This could further degrade due to inadequate maintenance of canal network, ongoing secondary soil salinization and waterlogging, worsening of groundwater quality. Large patches of low productivity in irrigation commands are occurring due to waterlogging and salt-affected soil, particularly in the scarcity rainfall year. Satellite remote sensing has been used for mapping of areas of low crop productivity, waterlogging and salt in irrigation commands. The spatial results obtained for these problems so far are less reliable for further use due to rapid change in soil quality parameters over the years. The existing spatial databases of canal network and flow data, groundwater quality and salt-affected soil were obtained from the central and state line departments/agencies and were integrated with GIS. Therefore, an integrated methodology based on remote sensing and GIS has been developed in ArcGIS environment on the basis of canal supply status, groundwater quality, salt-affected soils, and satellite-derived vegetation index (NDVI), salinity index (NDSI) and waterlogging index (NSWI). This methodology was tested for identification and delineation of area of low productivity in the Gautam Buddha Nagar district (Uttar Pradesh). It was found that the area affected by this problem lies mainly in Dankaur and Jewar blocks of the district. The problem area was verified with ground data and was found to be approximately 78% accurate. The methodology has potential to be used in other irrigation commands in the country to obtain reliable spatial data on low crop productivity.

Keywords: remote sensing, GIS, salt affected soil, crop productivity, Gautam Buddha Nagar

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

Abstract:

To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

Procedia PDF Downloads 412

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 232

Authors: Hamza Benzerrouk, Alexander Nebylov

Abstract:

In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

Procedia PDF Downloads 280

Authors: Fabricio Costa Silva, Samuel Xavier de Souza

Abstract:

A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, complexity, parallelism

Procedia PDF Downloads 538