Search results for: unmanned autonomous air vehicle

Authors: Ajin Frank J., Shridevi Jeevan Kamble

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The primary objective of this research paper is to identify significant patterns and insights in road accident data in India spanning from 2016 to 2021. The study reveals that the frequency of accidents, injuries, and fatalities varies depending on numerous factors such as the type of vehicle, time of accidents, age of the vehicle, age and gender of the driver, among others. Notably, the COVID-19 pandemic and subsequent lockdown measures have significantly impacted these figures. One of the key findings of the analysis is the rise in the number of accidents and deaths involving two-wheeler vehicles, particularly among younger individuals, in major states across India. This trend is of concern, and there is a need for increased awareness and precautions to prevent these types of accidents. Additionally, with the imminent rise of electric vehicles in the coming years, ensuring their safety on the road is a critical matter. Another significant factor contributing to road accidents is the age of vehicles. As vehicles age, their handling becomes more challenging compared to new ones, increasing the risk of accidents. Thus, it is imperative for the government to impose stringent regulations and laws to reduce these accident-causing factors and raise awareness among individuals about taking necessary precautions to avoid accidents. This study highlights the importance of understanding the underlying patterns and factors contributing to road accidents in India. Through this knowledge, policymakers and stakeholders can develop effective strategies to address these challenges and promote road safety, ultimately reducing the number of accidents, injuries, and fatalities on Indian roads.

Keywords: road accidents, India, road safety, accident deaths

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Authors: James Rate, Apostolos Pesiridis

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In this paper, the propulsion requirements required to achieve sustained hypersonic flight for commercial air transportation are evaluated. In addition, a design methodology is developed and used to determine the propulsive capabilities of both ramjet and scramjet engines. Twelve configurations are proposed for hypersonic flight using varying combinations of turbojet, turbofan, ramjet and scramjet engines. The optimal configuration was determined based on how well each of the configurations met the projected requirements for hypersonic commercial transport. The configurations were separated into four sub-configurations each comprising of three unique derivations. The first sub-configuration comprised four afterburning turbojets and either one or two ramjets idealised for Mach 5 cruise. The number of ramjets required was dependent on the thrust required to accelerate the vehicle from a speed where the turbojets cut out to Mach 5 cruise. The second comprised four afterburning turbojets and either one or two scramjets, similar to the first configuration. The third used four turbojets, one scramjet and one ramjet to aid acceleration from Mach 3 to Mach 5. The fourth configuration was the same as the third, but instead of turbojets, it implemented turbofan engines for the preliminary acceleration of the vehicle. From calculations which determined the fuel consumption at incremental Mach numbers this paper found that the ideal solution would require four turbojet engines and two Scramjet engines. The ideal mission profile was determined as being an 8000km sortie based on an averaging of popular long haul flights with strong business ties, which included Los Angeles to Tokyo, London to New York and Dubai to Beijing. This paper deemed that these routes would benefit from hypersonic transport links based on the previously mentioned factors. This paper has found that this configuration would be sufficient for the 8000km flight to be completed in approximately two and a half hours and would consume less fuel than Concord in doing so. However, this propulsion configuration still result in a greater fuel cost than a conventional passenger. In this regard, this investigation contributes towards the specification of the engine requirements throughout a mission profile for a hypersonic passenger vehicle. A number of assumptions have had to be made for this theoretical approach but the authors believe that this investigation lays the groundwork for appropriate framing of the propulsion requirements for sustained hypersonic flight for commercial air transportation. Despite this, it does serve as a crucial step in the development of the propulsion systems required for hypersonic commercial air transportation. This paper provides a methodology and a focus for the development of the propulsion systems that would be required for sustained hypersonic flight for commercial air transportation.

Keywords: hypersonic, ramjet, propulsion, Scramjet, Turbojet, turbofan

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Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias

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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.

Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution

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Authors: Ebrahim Hassan Kapeel, Ahmed Mohsen Kamel, Hossan Hendy, Yehia Z. Elhalwagy

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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control lawisdesigned for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: UAV dynamic model, attitude control, nonlinear PID, dynamic inversion

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Natalia Fontes De Oliveira

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The Canadian author Margaret Atwood deconstructs the tainted dichotomies between women and men by embracing the disorder throughout her dystopias. In Atwood’s The Testaments, nature can be seen as a background to the story as well as a metaphorical expression of the characters’ state of mind, nevertheless, the protagonists’ nature writing portrays conveys a curiosity to the pre-established sanctions of a docile garden, viewing nature as an autonomous entity, especially when they are away from the confinements of Gilead’s regime. The three narrating protagonists, Agnes, Aunt Lydia, and Nicole, use nature writing subversively as a form of rebellion. This paper investigates how the three protagonists narrate nature through an intimist point of view, with sensibility to observe the multiple relationships among humanity, nature, and the impositions of a theocratic ultra conservative patriarchal society.

Keywords: contemporary literature, dystopias, feminism, women’s writing

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Authors: Lucjan Setlak, Emil Ruda

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The subject of this paper is to review, comparative analysis and simulation of selected components of power electronic systems (PES), consistent with the concept of a more electric aircraft (MEA). Comparative analysis and simulation in software environment MATLAB / Simulink were carried out based on a group of representatives of civil aircraft (B-787, A-380) and military (F-22 Raptor, F-35) in the context of multi-pulse converters used in them (6- and 12-pulse, and 18- and 24-pulse), which are key components of high-tech electronics on-board power systems of autonomous power systems (ASE) of modern aircraft (airplanes of the future).

Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems)

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Salvador Antelmo Casanova Valencia

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This study documents the use of the Minecraft Education Edition application to explore immersive game-based learning environments. We analyze the contributions of fourth-year university students who are pursuing a degree in Administrative Computing at the Universidad Michoacana de San Nicolas de Hidalgo. In this study, descriptive data and statistical inference are detailed using a quasi-experimental design using the Wilcoxon test. The instruments will provide data validation. Game-based learning in immersive environments necessarily implies greater student participation and commitment, resulting in the study, motivation, and significant improvements, promoting cooperation and autonomous learning.

Keywords: game-based learning, gamification, higher education, Minecraft

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang

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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.

Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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Authors: P. Tanuska, A. Elias, P. Vazan, B. Zahradnikova

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This article describes the information system for measuring and evaluating the dose rate in the environment of nuclear power plants Mochovce and Bohunice in Slovakia. The article presents the results achieved in the implementation of the EU project–Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants. The objectives included improving the system of acquisition, measuring and evaluating data with mobile and autonomous units applying new knowledge from research. The article provides basic and specific features of the system and compared to the previous version of the system, also new functions.

Keywords: information system, dose rate, mobile devices, nuclear power plant

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Authors: Salaheddine Bendak, Sara S. Alnaqbi

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The seat belt is a vital tool in improving traffic safety conditions and minimising injuries due to traffic accidents. Most developing countries are facing a big problems associated with the human and financial losses due to traffic accidents. One way to minimise these losses is the use of seat belts by passengers both in the front and rear seats of a vehicle; however, at the same time, close to nothing is known about the rates of seat belt utilisation among rear seat passengers in many developing countries. Therefore, there is a need to estimate these rates in order to know the extent of this problem and how people interact with traffic safety measures like seat belts and find demographic characteristics that contribute to wearing or non-wearing of seat belts with the aim of finding solutions to improve wearing rates. In this paper, an observational study was done to gather data on restraints use in motor vehicle rear seats in eight observational stations in a rapidly developing country, the United Arab Emirates (UAE), and estimate a use rate for the whole country. Also, a questionnaire was used in order to study demographic characteristics affecting the wearing of seatbelts in rear seats. Results of the observational study showed that the overall wearing/usage rate was 12.3%, which is considered very low when compared to other countries. Survey results show that single, male, less educated passengers from Arab and South Asian backgrounds use seat belts reportedly less than others. Finally, solutions are put forward to improve this wearing rate based on the results of this study.

Keywords: Seat belts, traffic crashes, United Arab Emirates, rear seats

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Authors: Mohamed Moheyeldin Mahmoud

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Various Islamic, Coptic and Jewish archeological places are located in many Egyptian neighborhoods such as Alsayeda zainab, Aldarb Alahmar, Algammaleya and many other in which they are daily exposed to a great traffic intensity causing vibrations. Vibrations could be stated as one of the most important challenges that face the archeological buildings and threaten their survival. The impact of vibrations varies according to the nature of the soil, nature and building conditions, how far the source of vibration is and the period of exposure. Traffic vibrations could be also stated as one of the most common types of vibrations having the greatest impact on buildings and archaeological installations. These vibrations result from the way that the vehicles act with different types of roads which vary according to the shape, nature, and type of obstacles. Other elements concerning the vehicle itself such as speed, weight, and load have a direct impact on the vibrations resulting from the vehicle movement that couldn't be neglected. The research aims to determine some of the requirements that must be observed when designing the public means of transport operating in the archaeological areas, in order to preserve the archaeological nature of the place. The research concludes that light weight slow motion vehicles should be used (25-50 km/h at maximum) having a multi-leaf steel spring suspension system instead of having an air-bag one should be used in order to reduce generated vibrations that could destroy the archeological buildings. Isolation layers could be used in the engine chamber in order to reduce the resulting noise causing vibrations. Electrically operated engines that use solar photovoltaic cells as a source of electricity could be used instead of gas ones in order to reduce the resulting engine noise.

Keywords: archeological, design, isolation layers, suspension, vibrations

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Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Jean Felix Tuyisingize

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Speeding or inappropriate speed is a major problem worldwide, contributing to 10-15% of road crashes and 30% of fatal injury crashes. The consequences of speeding put the driver's life at risk and the lives of other road users like motorists, cyclists, and pedestrians. To control vehicle speeds, governments, and traffic authorities enforced speed regulations through speed cameras and speed section control, which monitor all vehicle speeds and detect plate numbers to levy penalties. However, speed limit violations are prevalent, even on motorways with speed cameras. The problem with speed cameras is that they alter driver behaviors, and their effect declines with increasing distance from the speed camera location. Drivers decelerate short distances before the camera and vigorously accelerate above the speed limit just after passing by the camera. The sudden decelerating near cameras causes the drivers to try to make up for lost time after passing it, and they do this by speeding up, resulting in a phenomenon known as the "Kangaroo jump" or "V-profile" around camera/ASSC areas. This study investigated the impact of speed enforcement devices, specifically Average Speed Section Control (ASSCs) and fixed cameras, on acceleration and deceleration events within their vicinity. The research employed advanced statistical and Geographic Information System (GIS) analysis on naturalistic driving data, to uncover speeding patterns near the speed enforcement systems. The study revealed a notable concentration of events within a 600-meter radius of enforcement devices, suggesting their influence on driver behaviors within a specific range. However, most of these events are of low severity, suggesting that drivers may not significantly alter their speed upon encountering these devices. This behavior could be attributed to several reasons, such as consistently maintaining safe speeds or using real-time in-vehicle intervention systems. The complexity of driver behavior is also highlighted, indicating the potential influence of factors like traffic density, road conditions, weather, time of day, and driver characteristics. Further, the study highlighted that high-severity events often occurred outside speed enforcement zones, particularly around intersections, indicating these as potential hotspots for drastic speed changes. These findings call for a broader perspective on traffic safety interventions beyond reliance on speed enforcement devices. However, the study acknowledges certain limitations, such as its reliance on a specific geographical focus, which may impact the broad applicability of the findings. Additionally, the severity of speed modification events was categorized into low, medium, and high, which could oversimplify the continuum of speed changes and potentially mask trends within each category. This research contributes valuable insights to traffic safety and driver behavior literature, illuminating the complexity of driver behavior and the potential influence of factors beyond the presence of speed enforcement devices. Future research directions may employ various categories of event severity. They may also explore the role of in-vehicle technologies, driver characteristics, and a broader set of environmental variables in driving behavior and traffic safety.

Keywords: acceleration, deceleration, speeding, inappropriate speed, speed enforcement cameras

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Authors: Swapnil Singh, Sanjoy Das

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Mobile Ad-Hoc Network (MANET) is infrastructure less networks dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depends on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper, we survey various energy efficient routing protocol. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.

Keywords: delaunay triangulation, deployment, energy efficiency, MANET

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Authors: Yasuyo Makido, Vivek Shandas, David J. Sailor, M. Salim Ferwati

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Mitigating extreme urban heat is challenging in a desert climate such as Doha, Qatar, since outdoor daytime temperature area often too high for the human body to tolerate. Recent studies demonstrate that cities in arid and semiarid areas can exhibit ‘urban cool islands’ - urban areas that are cooler than the surrounding desert. However, the variation of temperatures as a result of the time of day and factors leading to temperature change remain at the question. To address these questions, we examined the spatial and temporal variation of air temperature in Doha, Qatar by conducting multiple vehicle-base local temperature observations. We also employed three statistical approaches to model surface temperatures using relevant predictors: (1) Ordinary Least Squares, (2) Regression Tree Analysis and (3) Random Forest for three time periods. Although the most important determinant factors varied by day and time, distance to the coast was the significant determinant at midday. A 70%/30% holdout method was used to create a testing dataset to validate the results through Pearson’s correlation coefficient. The Pearson’s analysis suggests that the Random Forest model more accurately predicts the surface temperatures than the other methods. We conclude with recommendations about the types of development patterns that show the greatest potential for reducing extreme heat in air climates.

Keywords: desert cities, tree-structure regression model, urban cool Island, vehicle temperature traverse

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Authors: Karthikeyan Kalirajan, Ashok Joshi

Abstract:

An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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Authors: Abdul Azarrudin M. A., Pothiraj K., Kandasamy Satish

Abstract:

In the current automobile scenario, there comes a demand on more sophistication and comfort drive feel on passenger segments. The clutch pedal effort is one such customer touch feels in manual transmission vehicles, where the driver continuous to operate the clutch pedal in his entire the driving maneuvers. Hence optimum pedal efforts at green condition and over mileage to be ensured for fatigue free the driving. As friction is one the predominant factor and its tendency to challenge the technicality by causing the function degradation. One such semi-hydraulic systems shows load efficiency of about 70-75% over lifetime only due to the increase in friction which leads to the increase in pedal effort and cause fatigue to the vehicle driver. This work deals with the study of friction with different interfaces and its influence in the fulcrum points over mileage, with the objective of understanding the trend over mileage and determining the alternative ways of resolving it. In that one way of methodology is the reduction of friction by experimental investigation of various friction reduction interfaces like metal-to-metal interface and it has been tried out and is detailed further. Also, the specific attention has been put up considering the fulcrum load and its contact interfaces to move on with this study. The main results of the experimental data with the influence of three different contact interfaces are being presented with an ultimate intention of ending up into less fatigue with longer consistent pedal effort, thus smoothens the operation of the end user. The Experimental validation also has been done through rig-level test setup to depict the performance at static condition and in-parallel vehicle level test has also been performed to record the additional influences if any.

Keywords: automobile, clutch, friction, fork

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Authors: Dan Ohev Zion, Alon Cohen

Abstract:

In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.

Keywords: radar, FMCW Radar, IQ mismatch, six port

Procedia PDF Downloads 152

Authors: Vedansh More, Lalatendu Bal, Ronak Panchal, Atharva Kulkarni

Abstract:

The project aims at developing a cost-effective test bench capable of testing and validating the complete powertrain package of an electric vehicle. Emrax 228 high voltage synchronous motor was selected as the prime mover for study. A tandem type dynamometer comprising of two loading methods; inertial, using standard inertia rollers and absorptive, using a separately excited DC generator with resistive coils was developed. The absorptive loading of the prime mover was achieved by implementing a converter circuit through which duty of the input field voltage level was controlled. This control was efficacious in changing the magnetic flux and hence the generated voltage which was ultimately dropped across resistive coils assembled in a load bank with all parallel configuration. The prime mover and loading elements were connected via a chain drive with a 2:1 reduction ratio which allows flexibility in placement of components and a relaxed rating of the DC generator. The development will aid in determination of essential characteristics like torque-RPM, power-RPM, torque factor, RPM factor, heat loads of devices and battery pack state of charge efficiency but also provides a significant financial advantage over existing versions of dynamometers with its cost-effective solution.

Keywords: absorptive load, chain drive, chordal action, DC generator, dynamometer, electric vehicle, inertia rollers, load bank, powertrain, pulse width modulation, reduction ratio, road load, testbench

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Authors: Indu Barwal, Shloka Thakur, Subhash C. Yadav

Abstract:

The plant virus capsid protein based nanoparticles are extensively studied for their application in biomedical research for development of nanomedicines and drug delivery systems. We have developed a chimeric drug delivery system by controlled in vitro assembly of separately bioconjugated fluorescent dye (as reporting molecule), folic acid (as receptor binding biomolecule for targeted delivery) and doxorubicin (as anticancer drug) using modified EDC NHS chemistry on heterologously overexpressed (E. coli) capsid proteins of cowpea chlorotic mottle virus (CCMV). This chimeric vehicle was further encapsidated on gold nanoparticles (20nm) coated with 5≠ thiolated DNA probe to neutralize the positive charge of capsid proteins. This facilitates the in vitro assembly of modified capsid subunits on the gold nanoparticles to develop chimeric GNPs encapsidated targeted drug delivery system. The bioconjugation of functionalities, number of functionality on capsid subunits as well as virus like nanoparticles, structural stability and in vitro assembly were confirmed by SDS PAGE, relative absorbance, MALDI TOF, ESI-MS, Circular dichroism, intrinsic tryptophan fluorescence, zeta particle size analyzer and TEM imaging. This vehicle was stable at pH 4.0 to 8.0 suitable for many organelles targeting. This in vitro assembled chimeric plant virus like particles could be suitable for ideal drug delivery vehicles for subcutaneous cancer treatment and could be further modified for other type of cancer treatment by conjugating other functionalities (targeting, drug) on capsids.

Keywords: chimeric drug delivery vehicles, bioconjugated plant, virus, capsid

Procedia PDF Downloads 493

Authors: Jigar N. Shah, Hiral J. Shah, Praful D. Bharadia

Abstract:

The major challenge faced by formulation scientists in transdermal drug delivery system is to overcome the inherent barriers related to skin permeation. The stratum corneum layer of the skin is working as the rate limiting step in transdermal transport and reduce drug permeation through skin. Many approaches have been used to enhance the penetration of drugs through this layer of the skin. The purpose of this study is to investigate the development and evaluation of a combined approach of drug carriers and iontophoresis as a vehicle to improve skin permeation of an analgesic drug. Iontophoresis is a non-invasive technique for transporting charged molecules into and through tissues by a mild electric field. It has been shown to effectively deliver a variety of drugs across the skin to the underlying tissue. In addition to the enhanced continuous transport, iontophoresis allows dose titration by adjusting the electric field, which makes personalized dosing feasible. Drug carrier could modify the physicochemical properties of the encapsulated molecule and offer a means to facilitate the percutaneous delivery of difficult-to-uptake substances. Recently, there are some reports about using liposomes, microemulsions and polymeric nanoparticles as vehicles for iontophoretic drug delivery. Niosomes, the nonionic surfactant-based vesicles that are essentially similar in properties to liposomes have been proposed as an alternative to liposomes. Niosomes are more stable and free from other shortcoming of liposomes. Recently, the transdermal delivery of certain drugs using niosomes has been envisaged and niosomes have proved to be superior transdermal nanocarriers. Proniosomes overcome some of the physical stability related problems of niosomes. The proniosomal structure was liquid crystalline-compact niosomes hybrid which could be converted into niosomes upon hydration. The combined use of drug carriers and iontophoresis could offer many additional benefits. The system was evaluated for Encapsulation Efficiency, vesicle size, zeta potential, Transmission Electron Microscopy (TEM), DSC, in-vitro release, ex-vivo permeation across skin and rate of hydration. The use of proniosomal gel as a vehicle for the transdermal iontophoretic delivery was evaluated in-vitro. The characteristics of the applied electric current, such as density, type, frequency, and on/off interval ratio were observed. The study confirms the synergistic effect of proniosomes and iontophoresis in improving the transdermal permeation profile of selected analgesic drug. It is concluded that proniosomal gel can be used as a vehicle for transdermal iontophoretic drug delivery under suitable electric conditions.

Keywords: iontophoresis, niosomes, permeation enhancement, transdermal delivery

Procedia PDF Downloads 379