Search results for: tracking and cloud

Authors: Jia Li, Huacong Li, Xiaobao Han

Abstract:

Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

Procedia PDF Downloads 296

Authors: Oliver Ohneiser, Francesca De Crescenzio, Gianluca Di Flumeri, Jan Kraemer, Bruno Berberian, Sara Bagassi, Nicolina Sciaraffa, Pietro Aricò, Gianluca Borghini, Fabio Babiloni

Abstract:

An increasing degree of automation in air traffic will also change the role of the air traffic controller (ATCO). ATCOs will fulfill significantly more monitoring tasks compared to today. However, this rather passive role may lead to Out-Of-The-Loop (OOTL) effects comprising vigilance decrement and less situation awareness. The project MINIMA (Mitigating Negative Impacts of Monitoring high levels of Automation) has conceived a system to control and mitigate such OOTL phenomena. In order to demonstrate the MINIMA concept, an experimental simulation set-up has been designed. This set-up consists of two parts: 1) a Task Environment (TE) comprising a Terminal Maneuvering Area (TMA) simulator as well as 2) a Vigilance and Attention Controller (VAC) based on neurophysiological data recording such as electroencephalography (EEG) and eye-tracking devices. The current vigilance level and the attention focus of the controller are measured during the ATCO’s active work in front of the human machine interface (HMI). The derived vigilance level and attention trigger adaptive automation functionalities in the TE to avoid OOTL effects. This paper describes the full-scale experimental set-up and the component development work towards it. Hence, it encompasses a pre-test whose results influenced the development of the VAC as well as the functionalities of the final TE and the two VAC’s sub-components.

Keywords: automation, human factors, air traffic controller, MINIMA, OOTL (Out-Of-The-Loop), EEG (Electroencephalography), HMI (Human Machine Interface)

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

Abstract:

Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

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Authors: Baha-Aldeen S. Algmati, Ahmed R. Ballil

Abstract:

Multiphase flows occur widely in many engineering and industrial processes as well as in the environment we live in. In particular, bubbly flows are considered to be crucial phenomena in fluid flow applications and can be studied and analyzed experimentally, analytically, and computationally. In the present paper, the dynamic motion of an air bubble rising within a column of liquid is numerically simulated using an open-source CFD modeling tool 'OpenFOAM'. An interface tracking numerical algorithm called MULES algorithm, which is built-in OpenFOAM, is chosen to solve an appropriate mathematical model based on the volume of fluid (VOF) numerical method. The bubbles initially have a spherical shape and starting from rest in the stagnant column of liquid. The algorithm is initially verified against numerical results and is also validated against available experimental data. The comparison revealed that this algorithm provides results that are in a very good agreement with the 2D numerical data of other CFD codes. Also, the results of the bubble shape and terminal velocity obtained from the 3D numerical simulation showed a very good qualitative and quantitative agreement with the experimental data. The simulated rising bubbles yield a very small percentage of error in the bubble terminal velocity compared with the experimental data. The obtained results prove the capability of OpenFOAM as a powerful tool to predict the behavior of rising characteristics of the spherical bubbles in the stagnant column of liquid. This will pave the way for a deeper understanding of the phenomenon of the rise of bubbles in liquids.

Keywords: CFD simulations, multiphase flows, OpenFOAM, rise of bubble, volume of fluid method, VOF

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Authors: Abhimanyu Thakur, Youngjin Lee

Abstract:

Glioma is a lethal brain cancer whose early diagnosis and prognosis are limited due to the dearth of a suitable technique for its early detection. Current approaches, including magnetic resonance imaging (MRI), computed tomography (CT), and invasive biopsy for the diagnosis of this lethal disease, hold several limitations, demanding an alternative method. Recently, extracellular vesicles (EVs) have been used in numerous biomarker studies, majorly exosomes and microvesicles (MVs), which are found in most of the cells and biofluids, including blood, cerebrospinal fluid (CSF), and urine. Remarkably, glioma cells (GMs) release a high number of EVs, which are found to cross the blood-brain-barrier (BBB) and impersonate the constituents of parent GMs including protein, and lncRNA; however, biophysical properties of EVs have not been explored yet as a biomarker for glioma. We isolated EVs from cell culture conditioned medium of GMs and regular primary culture, blood, and urine of wild-type (WT)- and glioma mouse models, and characterized by nano tracking analyzer, transmission electron microscopy, immunogold-EM, and differential light scanning. Next, we measured the biophysical parameters of GMs-EVs by using atomic force microscopy. Further, the functional constituents of EVs were examined by FTIR and Raman spectroscopy. Exosomes and MVs-derived from GMs, blood, and urine showed distinction biophysical parameters (roughness, adhesion force, and stiffness) and different from that of regular primary glial cells, WT-blood, and -urine, which can be attributed to the characteristic functional constituents. Therefore, biophysical features can be potential diagnostic biomarkers for glioma.

Keywords: glioma, extracellular vesicles, exosomes, microvesicles, biophysical properties

Procedia PDF Downloads 125

Authors: C. Chaillou

Abstract:

The dominant theoretical approaches in Criminology are interested in the phenomenon of delinquency from the question of the management of the risks incurred by the population. Thus, this research advocate prevention of this phenomenon by a tracking of early disorders in children. Treatments offered to rely on medical research (genetics and biology are cited as a reference) and assuming a high naturalization of delinquent behaviour. Programs that are offered also reduce to a recovery of the deviant behaviour, and rely readily on behavioral guidelines, with an educational grant. Public policy then rely on these programs to prevent unwanted behaviour within a given population and to reduce the risk for the company. This is the case in France, with national institutes making (juvenile) violence a public health problem. We consider that other approaches, issues of sociology, are more relevant to the treatment of offenders. These approaches are moving, not on its prevention, but from its inputs and its outputs. Several modalities of entries and exits of delinquency can find and analyze in terms of process. We assume that there is a dynamic inherent in the individual and it is important to take into account the environment of the offender. These different types of processes can illuminate from the derived work of the Psychoanalytical psychopathology and lead to more effective treatment of delinquent acts. Psychoanalytic concepts have enabled us to offer a new look means to treat delinquency, placing several types of relationship with the other and relating to the clinical structure and the uniqueness of the case, we have been able to enter subjective and unconscious logics at work in delinquent acts. This research has facilitated the reduction of these types of subjective responses and proposed others, opening to a reintegration of offenders in a social link them being more favourable and in a longer term.

Keywords: delinquency, insertion, social link, unconscious

Procedia PDF Downloads 367

Authors: R. Hellmuth

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The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

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Authors: Sharda Kumari, Saiman Shetty

Abstract:

Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

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Authors: Chong Zhang

Abstract:

There is widespread debate about the nationalistic top-down approach to citizenship education. Employing the notion of cultural citizenship as a useful theoretical lens, citizenship education research tends to focus on the process of subjectivity construction among students’ citizenship learning process. As the Communist Party of China (CPC) plays a dominant role in cultivating citizens through ideological and political education (IaPE) in Chinese universities, the research problem herein focuses on the dynamics and complexity of how Chinese university students construct their subjectivities regarding citizenship learning through IaPE, mediated by the interaction between the state and university teachers. Drawing on questionnaire data from 212 students and interview data from 25 students in one university in China, this paper examines the ways in which students understand and respond to dominant discourses. Its findings reveal there is a deficit of citizenship learning in IaPE, and that students feel ideologically pressurized. From its analysis of social contexts’ influence, the article suggests Chinese higher education students act as either mild changemakers or active self-motivators to enact complex subjectivities, in that they must involve themselves in IaPE for personal academic and career development, yet adopt covert strategies to realise their self-conscious citizenship learning expectations. These strategies take the form of passive and active freedoms, ranging from obediently completing basic curriculum requirements and distancing themselves by studying abroad, to actively searching for learning opportunities from other courses and social media. This paper contributes to the research on citizenship education by recognizing the complexities of how subjectivities are formed in formal university settings.

Keywords: university students, citizenship learning, cultural citizenship, subjectivity, Chinese higher education

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar

Abstract:

Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.

Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt

Procedia PDF Downloads 553

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

Procedia PDF Downloads 1155

Authors: Linnan Zhang

Abstract:

Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

Procedia PDF Downloads 175

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

Procedia PDF Downloads 375

Authors: Vaishakh Medikeri

Abstract:

Lightning, the marvelous, spectacular and the awesome truth of nature is one of the greatest energy sources left unharnessed since ages. A single lightning bolt of lightning contains energy of about 15 billion joules. This huge amount of energy cannot be harnessed completely but partially. This paper proposes to harness the energy from lightning strikes. Throughout the globe the frequency of lightning is 40-50 flashes per second, totally 1.4 billion flashes per year; all of these flashes carrying an average energy of about 15 billion joules each. When a lightning bolt strikes the ground, tremendous amounts of energy is transferred to earth which propagates in the form of concentric circular energy waves. These waves have a frequency of about 7.83Hz. Harvesting the lightning bolt directly seems impossible, but harvesting the energy waves produced by the lightning is pretty easier. This can be done using a tricoil energy harnesser which is a new device which I have invented. We know that lightning bolt seeks the path which has minimum resistance down to the earth. For this we can make a lightning rod about 100 meters high. Now the lightning rod is attached to the tricoil energy harnesser. The tricoil energy harnesser contains three coils whose centers are collinear and all the coils are parallel to the ground. The first coil has one of its ends connected to the lightning rod and the other end grounded. There is a secondary coil wound on the first coil with one of its end grounded and the other end pointing to the ground and left unconnected and placed a little bit above the ground so that this end of the coil produces more intense currents, hence producing intense energy waves. The first coil produces very high magnetic fields and induces them in the second and third coils. Along with the magnetic fields induced by the first coil, the energy waves which are currents also flow through the second and the third coils. The second and the third coils are connected to a generator which in turn is connected to a capacitor which stores the electrical energy. The first coil is placed in the middle of the second and the third coil. The stored energy can be used for transmission of electricity. This new technique of harnessing the lightning strikes would be most efficient in places with more probability of the lightning strikes. Since we are using a lightning rod sufficiently long, the probability of cloud to ground strikes is increased. If the proposed apparatus is implemented, it would be a great source of pure and clean energy.

Keywords: generator, lightning rod, tricoil energy harnesser, harvesting energy

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Ilze Pelece, Imants Ziemelis, Henriks Putans

Abstract:

Traditionally the solar energy has been used in southern countries, but it has been used also in northern ones. Most popular kind of use of solar energy in Latvia is solar collector for water heating. Traditionally flat-plate solar collectors are used because of simplicity of manufacturing. However, some peculiarities in use of solar energy in northern countries must be taken into account. In northern countries, there is lower irradiance, but longer day and longer path of the sun during summer. Therefore traditional flat-plate solar collectors are not appropriate enough in northern countries, but new forms must be developed. There are two forms of solar collectors - cylindrical and semi-spherical – proposed in this work. Such collectors can be made both for water or air heating. Theoretical calculations and measurements of energy gain from those two collectors have been done. Results show that daily energy sum received by the semi-spherical collector from the sun at the middle of summer is 1.43 times more than that of the flat one, but for the cylindrical collector, it is 1.74 times more than that of the flat one or equal to that of the tracking to sun flat-plate collector. The resulting difference in energy gain from collector will be not so large because of the difference in heat loses. Heat can be decreased by switching off the water circulation pump when the sun is covered by clouds. For this purpose solar batteries, powered pump can be used instead of complicated and expensive automatics. Even more important than overall energy gain is the fact that semi-spherical and cylindrical collectors work all day (17 hours in the middle of summer at 57 northern latitudes), while flat-plate collector only about 11 hours. Yearly energy sum received by the collector from the sun is 1.5 and 1.9 times larger for the semi-spherical and cylindrical collector respectively as for the flat one. The cylindrical solar collector is easier to manufacture, but semi-spherical one is more aesthetical and durable against the impact of the wind. Although solar collectors for water and air heating are studied in this article, main ideas are applicable also for solar batteries.

Keywords: cylindric, semi-spherical, solar collector, solar energy, water heating

Procedia PDF Downloads 244

Authors: Hai Zeng, Yisheng Li, Jincheng Huang, Chenghui Huang, Ying Zhang

Abstract:

Children are strong; the country strong, the development of children Basketball is a strategic advantage. Common forms of basketball equipment has been difficult to meet the needs of young children teaching the game of basketball, basketball development for 3-6 years old children in the form of appropriate teaching aids is a breakthrough basketball game teaching children bottlenecks, improve teaching critical path pleasure, but also the development of early childhood basketball a necessary requirement. In this study, literature, questionnaires, focus group interviews, comparative analysis, for domestic and foreign use of 12 kinds of basketball teaching aids (cloud computing MINI basketball, adjustable basketball MINI, MINI basketball court, shooting assist paw print ball, dribble goggles, dribbling machine, machine cartoon shooting, rebounding machine, against the mat, elastic belt, ladder, fitness ball), from fun and improve early childhood shooting technique, dribbling technology, as well as offensive and defensive rebounding against technology conduct research on conversion technology. The results show that by using appropriate forms of teaching children basketball aids, can effectively improve children's fun basketball game, targeted to improve a technology, different types of aids from different perspectives enrich the connotation of children basketball game. Recommended for children of color psychology, cartoon and environmentally friendly material production aids, and increase research efforts basketball aids children, encourage children to sports teachers aids applications.

Keywords: health and physical education field of curriculum outline, health fitness, sports and health curriculum reform, Taiwan, twelve years basic education

Procedia PDF Downloads 375

Authors: Gichun Cha, Changgil Lee, Seunghee Park

Abstract:

The objective of the study is to construct the shape management method contributing to the safety of the large structure. In Korea, the research of the shape management is lack because of the new attempted technology. Terrestrial Laser Scanning (TLS) is used for measurements of large structures. TLS provides an efficient way to actively acquire accurate the point clouds of object surfaces or environments. The point clouds provide a basis for rapid modeling in the industrial automation, architecture, construction or maintenance of the civil infrastructures. TLS produce a huge amount of point clouds. Registration, Extraction and Visualization of data require the processing of a massive amount of scan data. The octree can be applied to the shape management of the large structure because the scan data is reduced in the size but, the data attributes are maintained. The octree space partitioning generates the voxel of 3D space, and the voxel is recursively subdivided into eight sub-voxels. The point cloud of scan data was converted to voxel and sampled. The experimental site is located at Sungkyunkwan University. The scanned structure is the steel-frame bridge. The used TLS is Leica ScanStation C10/C5. The scan data was condensed 92%, and the octree model was constructed with 2 millimeter in resolution. This study presents octree space partitioning for handling the point clouds. The basis is created by shape management of the large structures such as double-deck tunnel, building and bridge. The research will be expected to improve the efficiency of structural health monitoring and maintenance. "This work is financially supported by 'U-City Master and Doctor Course Grant Program' and the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIP) (NRF- 2015R1D1A1A01059291)."

Keywords: 3D scan data, octree space partitioning, shape management, structural health monitoring, terrestrial laser scanning

Procedia PDF Downloads 278

Authors: Gayatri Mahajan

Abstract:

Modern Construction Technology (CT) includes a broad range of advanced techniques and practices that bound the recent developments in material technology, design methods, quantity surveying, facility management, services, structural analysis and design, and other management education. Adoption of recent digital transformation technology is the need of today to speed up the business and is also the basis of construction improvement. Incorporating and practicing the technologies such as cloud-based communication and collaboration solution, Mobile Apps and 5G,3D printing, BIM and Digital Twins, CAD / CAM, AR/ VR, Big Data, IoT, Wearables, Blockchain, Modular Construction, Offsite Manifesting, Prefabrication, Robotic, Drones and GPS controlled equipment expedite the progress in the Construction industry (CI). Resources used are journaled research articles, web/net surfing, books, thesis, reports/surveys, magazines, etc. The outline of the research organization for this study is framed at four distinct levels in context to conceptualization, resources, innovative and emerging trends in CI, and better methods for completion of the construction projects. The present study conducted during 2020-2022 reveals that implementing these technologies improves the level of standards, planning, security, well-being, sustainability, and economics too. Application uses, benefits, impact, advantages/disadvantages, limitations and challenges, and policies are dealt with to provide information to architects and builders for smooth completion of the project. Results explain that construction technology trends vary from 4 to 15 for CI, and eventually, it reaches 27 for Civil Engineering (CE). The perspective of the most recent innovations, trends, tools, challenges, and solutions is highly embraced in the field of construction. The incorporation of the above said technologies in the pandemic Covid -19 and post-pandemic might lead to a focus on finding out effective ways to adopt new-age technologies for CI.

Keywords: BIM, drones, GPS, mobile apps, 5G, modular construction, robotics, 3D printing

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Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

Procedia PDF Downloads 75

Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

Procedia PDF Downloads 67

Authors: Mahsa Fathollahzadeh

Abstract:

The various nanoparticles employed in drug delivery applications include micelles, liposomes, solid lipid nanoparticles, polymeric nanoparticles, functionalized nanoparticles, nanocrystals, cyclodextrins, dendrimers, and nanotubes. Micelles, composed of amphiphilic block copolymers, can encapsulate hydrophobic molecules, allowing for targeted delivery. Liposomes, vesicular structures made up of phospholipids, can encapsulate both hydrophobic and hydrophilic molecules, providing a flexible platform for delivering therapeutic agents. Solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are designed to improve the stability and bioavailability of lipophilic drugs. Polymeric nanoparticles, such as poly(lactic-co-glycolic acid) (PLGA), are biodegradable and can be engineered to release drugs in a controlled manner. Functionalized nanoparticles, coated with targeting ligands or antibodies, can specifically target diseased cells or tissues. Nanocrystals, engineered to have specific surface properties, can enhance the solubility and bioavailability of poorly soluble drugs. Cyclodextrins, doughnut-shaped molecules with hydrophobic cavities, can be complex with hydrophobic molecules, allowing for improved solubility and bioavailability. Dendrimers, branched polymers with a central core, can be designed to deliver multiple therapeutic agents simultaneously. Nanotubes and metallic nanoparticles, such as gold nanoparticles, offer real-time tracking capabilities and can be used to detect biomolecular interactions. The use of these nanoparticles has revolutionized the field of drug delivery, enabling targeted and controlled release of therapeutic agents, reduced toxicity, and improved patient outcomes.

Keywords: nanotechnology, nanopharmaceuticals, drug-delivery, proteins, ligands, nanoparticles, chemistry

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Authors: Clémence Royer, Stéphane Mazouffre

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Nowadays, electric propulsion systems play a crucial role in space exploration missions due to their high specific impulse and long operational life. The Hall thrusters are one of the most mature EP technologies. It is a gridless ion thruster that has proved reliable and high-performance for decades in various space missions. Operation of HT relies on electron emissions through a cathode placed outside a hollow dielectric channel that includes an anode at the back. Negatively charged particles are trapped in a magnetic field and efficiently slow down. By collisions, the electron cloud ionizes xenon atoms. A large electric field is generated in the axial direction due to the low electron transverse mobility in the region of a strong magnetic field. Positive particles are pulled out of the chamber at high velocity and are neutralized directly at the exhaust area. This phenomenon leads to the acceleration of the spacecraft system at a high specific impulse. While HT’s architecture and operating principle are relatively simple, the physics behind thrust is complex and still partly unknown. Current and voltage oscillations, as well as electron properties, have been captured over a 30 mn time period after ignition. The observed low-frequency oscillations exhibited specific frequency ranges, amplitudes, and stability patterns. Correlations between the oscillations and plasma characteristics we analyzed. The impact of these instabilities on thruster performance, including thrust efficiency, has been evaluated as well. Moreover, strategies for mitigating and controlling these instabilities have been developed, such as filtering. In this contribution, in addition to presenting a summary of the results obtained in the transient regime, we will present and discuss recent advances in Hall thruster plasma discharge filtering and control.

Keywords: electric propulsion, Hall Thruster, plasma diagnostics, low-frequency oscillations

Procedia PDF Downloads 64

Authors: Mansa Radhakrishnan, Anwar Ali, Muhammad Rizwan Mughal

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Many universities around the world are working on modular and low budget architecture of small spacecraft to reduce the development cost of the overall system. This paper focuses on the design of a modular solar power harvesting system for a hexagonal-shaped small satellite. The designed solar power harvesting systems are composed of solar panels and power converter subsystems. The solar panel is composed of solar cells mounted on the external face of the printed circuit board (PCB), while the electronic components of power conversion are mounted on the interior side of the same PCB. The solar panel with dimensions 16.5cm × 99cm is composed of 36 solar cells (each solar cell is 4cm × 7cm) divided into four parallel banks where each bank consists of 9 solar cells. The output voltage of a single solar cell is 2.14V, and the combined output voltage of 9 series connected solar cells is around 19.3V. The output voltage of the solar panel is boosted to the satellite power distribution bus voltage level (28V) by a boost converter working on a constant voltage maximum power point tracking (MPPT) technique. The solar panel module is an eight-layer PCB having embedded coil in 4 internal layers. This coil is used to control the attitude of the spacecraft, which consumes power to generate a magnetic field and rotate the spacecraft. As power converter and distribution subsystem components are mounted on the PCB internal layer, therefore it is mandatory to do thermal analysis in order to ensure that the overall module temperature is within thermal safety limits. The main focus of the overall design is on compactness, miniaturization, and efficiency enhancement.

Keywords: small satellites, power subsystem, efficiency, MPPT

Procedia PDF Downloads 46

Authors: E. Rama Devi Jothilingam

Abstract:

Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

Procedia PDF Downloads 267

Authors: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

Abstract:

This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

Procedia PDF Downloads 139

Authors: Daniel F. Bohorquez, Luis M. Agudelo, Henry H. León

Abstract:

Heart rate variability (HRV) is defined as the temporary variation between heartbeats or RR intervals (distance between R waves in an electrocardiographic signal). This distance is currently a recognized biomarker. With the analysis of the distance, it is possible to assess the sympathetic and parasympathetic nervous systems. These systems are responsible for the regulation of the cardiac muscle. The analysis allows health specialists and researchers to diagnose various pathologies based on this variation. For the acquisition and analysis of HRV taken from a cardiac electrical signal, electronic equipment and analysis software that work independently are currently used. This complicates and delays the process of interpretation and diagnosis. With this delay, the health condition of patients can be put at greater risk. This can lead to an untimely treatment. This document presents a single portable device capable of acquiring electrocardiographic signals and calculating a total of 19 HRV metrics. This reduces the time required, resulting in a timelier intervention. The device has an electrocardiographic signal acquisition card attached to a microcontroller capable of transmitting the cardiac signal wirelessly to a mobile device. In addition, a mobile application was designed to analyze the cardiac waveform. The device calculates the RR and different metrics. The application allows a user to visualize in real-time the cardiac signal and the 19 metrics. The information is exported to a cloud database for remote analysis. The study was performed under controlled conditions in the simulated hospital of the Universidad de la Sabana, Colombia. A total of 60 signals were acquired and analyzed. The device was compared against two reference systems. The results show a strong level of correlation (r > 0.95, p < 0.05) between the 19 metrics compared. Therefore, the use of the portable system evaluated in clinical scenarios controlled by medical specialists and researchers is recommended for the evaluation of the condition of the cardiac system.

Keywords: biological signal análisis, heart rate variability (HRV), HRV metrics, mobile app, portable device.

Procedia PDF Downloads 167