Search results for: field data

Authors: Ali Azeem, Seung-Cheol Hong

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This study focuses on the epidemiological association between childhood leukaemia & adult brain cancer to offer strong evidence that extremely low-frequency magnetic field (ELF-MF) produced from power lines caused cancer. It also gives a comprehensive literature review on epidemiological studies of ELF-MF risk associated with HVTL and childhood leukaemia & adult brain cancer. From the literature review, it is concluded that there is a weak association present between ELF-MF and childhood leukaemia. No consistent association was present between brain cancer and ELF-MF. This study is done on Scielo data and PubMed using the terms extremely low-frequency magnetic field (ELF-MF+cancer), adult brain cancer, high power transmission lines, etc., for the past 10 years.

Keywords: childhood leukaemia, high voltage transmission lines, acute lymphoblastic leukaemia, power lines

Procedia PDF Downloads 221

Authors: Tatsuya Yamazaki, Kazuya Miyakawa, Tomohiko Sugiyama, Toshitaka Iwatani

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The introduction of sensor technologies into agriculture is a necessary step to realize Precision Agriculture. Although sensing methodologies themselves have been prevailing owing to miniaturization and reduction in costs of sensors, there are some difficulties to analyze and understand the sensing data. Targeting at pears ’Le Lectier’, which is particular to Niigata in Japan, cultivation environmental data have been collected at pear fields by eight sorts of sensors: field temperature, field humidity, rain gauge, soil water potential, soil temperature, soil moisture, inner-bag temperature, and inner-bag humidity sensors. With regard to the inner-bag temperature and humidity sensors, they are used to measure the environment inside the fruit bag used for pre-harvest bagging of pears. In this experiment, three kinds of fruit bags were used for the pre-harvest bagging. After over 100 days continuous measurement, volumes of sensing data have been collected. Firstly, correlation analysis among sensing data measured by respective sensors reveals that one sensor can replace another sensor so that more efficient and cost-saving sensing systems can be proposed to pear farmers. Secondly, differences in characteristic and performance of the three kinds of fruit bags are clarified by the measurement results by the inner-bag environmental sensing. It is found that characteristic and performance of the inner-bags significantly differ from each other by statistical analysis. Lastly, a relational model between the sensing data and the pear outlook quality is established by use of Structural Equation Model (SEM). Here, the pear outlook quality is related with existence of stain, blob, scratch, and so on caused by physiological impair or diseases. Conceptually SEM is a combination of exploratory factor analysis and multiple regression. By using SEM, a model is constructed to connect independent and dependent variables. The proposed SEM model relates the measured sensing data and the pear outlook quality determined on the basis of farmer judgement. In particularly, it is found that the inner-bag humidity variable relatively affects the pear outlook quality. Therefore, inner-bag humidity sensing might help the farmers to control the pear outlook quality. These results are supported by a large quantity of inner-bag humidity data measured over the years 2014, 2015, and 2016. The experimental and analytical results in this research contribute to spreading Precision Agriculture technologies among the farmers growing ’Le Lectier’.

Keywords: precision agriculture, pre-harvest bagging, sensor fusion, structural equation model

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Authors: Tonderai Muchenje, Xolani Mkhwanazi

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Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.

Keywords: precision agriculture, security, IoT, EIDE

Procedia PDF Downloads 86

Authors: Sheng-Po Tseng, Che-Hua Yang

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Motivation and Objective: Ultrasonic guided waves become an important tool for nondestructive evaluation of structures and components. Guided waves are used for the purpose of identifying defects or evaluating material properties in a nondestructive way. While guided waves are applied for evaluating material properties, instead of knowing the properties directly, preliminary signals such as time domain signals or frequency domain spectra are first revealed. With the measured ultrasound data, inversion calculation can be further employed to obtain the desired mechanical properties. Methods: This research is development of high speed inversion calculation technique for obtaining full-field mechanical properties from the quantitative laser ultrasound visualization system (QLUVS). The quantitative laser ultrasound visualization system (QLUVS) employs a mirror-controlled scanning pulsed laser to generate guided acoustic waves traveling in a two-dimensional target. Guided waves are detected with a piezoelectric transducer located at a fixed location. With a gyro-scanning of the generation source, the QLUVS has the advantage of fast, full-field, and quantitative inspection. Results and Discussions: This research introduces two important tools to improve the computation efficiency. Firstly, graphic procession unit (GPU) with large amount of cores are introduced. Furthermore, combining the CPU and GPU cores, parallel procession scheme is developed for the inversion of full-field mechanical properties based on the QLUVS data. The newly developed inversion scheme is applied to investigate the computation efficiency for single-layered and double-layered plate-like samples. The computation efficiency is shown to be 80 times faster than unparalleled computation scheme. Conclusions: This research demonstrates a high-speed inversion technique for the characterization of full-field material properties based on quantitative laser ultrasound visualization system. Significant computation efficiency is shown, however not reaching the limit yet. Further improvement can be reached by improving the parallel computation. Utilizing the development of the full-field mechanical property inspection technology, full-field mechanical property measured by non-destructive, high-speed and high-precision measurements can be obtained in qualitative and quantitative results. The developed high speed computation scheme is ready for applications where full-field mechanical properties are needed in a nondestructive and nearly real-time way.

Keywords: guided waves, material characterization, nondestructive evaluation, parallel processing

Procedia PDF Downloads 199

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

Procedia PDF Downloads 149

Authors: Yue Yan, Chang Nyung Kim

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The numerical investigation of the three-dimensional liquid-metal (LM) magnetohydrodynamic (MHD) flows in a curved duct with flow channel insert (FCI) is presented in this paper, based on the computational fluid dynamics (CFD) method. A uniform magnetic field is applied perpendicular to the duct. The interdependency of the flow variables is examined in terms of the flow velocity, current density, electric potential and pressure. The electromagnetic characteristics of the LM MHD flows are reviewed with an introduction of the electric-field component and electro-motive component of the current. The influence of the existence of the FCI on the fluid flow is investigated in detail. The case with FCI slit located near the side layer yields smaller pressure gradient with stable flow field.

Keywords: curved duct, flow channel insert, liquid-metal, magnetohydrodynamic

Procedia PDF Downloads 490

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

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Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 353

Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

Procedia PDF Downloads 98

Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun

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Due to the characteristics of high-heap and large-volume, the complex layers of waste and the high-water level of leachate, environmental pollution, and slope instability are easily produced. It is therefore of great significance to research the heterogeneous seepage field and stability of landfills. This paper focuses on the heterogeneous characteristics of the landfill piles and analyzes the seepage field and slope stability of the landfill using statistical and numerical analysis methods. The calculated results are compared with the field measurement and literature research data to verify the reliability of the model, which may provide the basis for the design, safe, and eco-friendly operation of the landfill. The main innovations are as follows: (1) The saturated-unsaturated seepage equation of heterogeneous soil is derived theoretically. The heterogeneous landfill is regarded as composed of infinite layers of homogeneous waste, and a method for establishing the heterogeneous seepage model is proposed. Then the formation law of the stagnant water level of heterogeneous landfills is studied. It is found that the maximum stagnant water level of landfills is higher when considering the heterogeneous seepage characteristics, which harms the stability of landfills. (2) Considering the heterogeneity weight and strength characteristics of waste, a method of establishing a heterogeneous stability model is proposed, and it is extended to the three-dimensional stability study. It is found that the distribution of heterogeneous characteristics has a great influence on the stability of landfill slope. During the operation and management of the landfill, the reservoir bank should also be considered while considering the capacity of the landfill.

Keywords: heterogeneous characteristics, leachate levels, saturated-unsaturated seepage, seepage field, slope stability

Procedia PDF Downloads 243

Authors: Jeryes Danial, Yosi Ben Asher

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Algorithms for controlling a swarm of robots is an active research field, out of which cattle herding is one of the most complex problems to solve. In this paper, we derive an independent herding algorithm that is specifically designed for a swarm of quadcopters. The algorithm works by devising flight trajectories that cause the cows to run-away in the desired direction and hence herd cows that are distributed in a given field towards a common gathering point. Unlike previously proposed swarm herding algorithms, this algorithm does not use a flocking model but rather stars each cow separately. The effectiveness of this algorithm is verified experimentally using a simulator. We use a special set of experiments attempting to demonstrate that the herding times of this algorithm correspond to field diameter small constant regardless of the number of cows in the field. This is an optimal result indicating that the algorithm groups the cows into intermediate groups and herd them as one forming ever closing bigger groups.

Keywords: swarm, independent, distributed, algorithm

Procedia PDF Downloads 171

Authors: Naima Jannat, Ariful Islam, Sharafat Hossain

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Due to the involvement of the large target volume, Craniospinal Irradiation makes it challenging to achieve a uniform dose, and it requires different isocenters. This isocentric junction needs to shift after every five fractions to overcome the possibility of hot and cold spots. This study aims to evaluate the Planning Target Volume coverage & sparing Organ at Risk between two techniques and shows that the Field Alignment Technique does not need replanning and resetting. Planning method for Craniospinal Irradiation by Eclipse treatment planning system Field Alignment and Extended Source to Surface Distance technique was developed where 36 Gy in 20 Fraction at the rate of 1.8 Gy was prescribed. The patient was immobilized in the prone position. In the Field Alignment technique, the plan consists of half beam blocked parallel opposed cranium and a single posterior cervicospine field was developed by sharing the same isocenter, which obviates divergence matching. Further, a single field was created to treat the remaining lumbosacral spine. Matching between the inferior diverging edge of the cervicospine field and the superior diverging edge of a lumbosacral field, the field alignment option was used, which automatically matches the field edge divergence as per the field alignment rule in Eclipse Treatment Planning System where the couch was set to 2700. In the Extended Source to Surface Distance technique, two parallel opposed fields were created for the cranium, and a single posterior cervicospine field was created where the Source to Surface Distance was from 120-140 cm. Dose Volume Histograms were obtained for each organ contoured and for each technique used. In all, the patient’s maximum dose to Planning Target Volume is higher for the Extended Source to Surface Distance technique to Field Alignment technique. The dose to all surrounding structures was increased with the use of a single Extended Source to Surface Distance when compared to the Field Alignment technique. The average mean dose to Eye, Brain Steam, Kidney, Oesophagus, Heart, Liver, Lung, and Ovaries were respectively (58% & 60 %), (103% & 98%), (13% & 15%), (10% & 63%), (12% & 16%), (33% & 30%), (14% & 18%), (69% & 61%) for Field Alignment and Extended Source to Surface Distance technique. However, the clinical target volume at the spine junction site received a less homogeneous dose with the Field Alignment technique as compared to Extended Source to Surface Distance. We conclude that, although the use of a single field Extended Source to Surface Distance delivered a more homogenous, but its maximum dose is higher than the Field Alignment technique. Also, a huge advantage of the Field Alignment technique for Craniospinal Irradiation is that it doesn’t need replanning and resetting up of patients after every five fractions and 95% prescribed dose was received by more than 95% of the Planning Target Volume in all the plane with the acceptable hot spot.

Keywords: craniospinalirradiation, cranium, cervicospine, immobilize, lumbosacral spine

Procedia PDF Downloads 108

Authors: Agata Zakrzewska, Dominik Kopeć, Adrian Ochtyra

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The growing number of new cameras, sensors, and research methods allow for a broader application of thermal data in remote sensing vegetation studies. The aim of this research was to check whether it is possible to use thermal infrared data with a spectral range (3.6-4.9 μm) obtained during the day and the night to assess the health condition of selected species of deciduous trees in an urban environment. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning, and orthophoto map images were collected. Synchronously with airborne data, ground reference data were obtained for 617 studied species (Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata, and Tilia × euchlora) in different health condition states. The results were as follows: (i) healthy trees are cooler than trees in poor condition and dying both in the daytime and nighttime data; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06oC of mean value on the nighttime data and 3.28oC of mean value on the daytime data; (iii) condition classes significantly differentiate on both daytime and nighttime thermal data, but only on daytime data all condition classes differed statistically significantly from each other. In conclusion, the aerial thermal data can be considered as an alternative to hyperspectral data, a method of assessing the health condition of trees in an urban environment. Especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health that should be visually checked in the field.

Keywords: middle wave infrared, thermal imagery, tree discoloration, urban trees

Procedia PDF Downloads 110

Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 229

Authors: Muhammad Ahsan

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The effective decommissioning of oil and gas fields and related assets is one of the most important challenges facing the oil and gas industry today and in the future. Decommissioning decisions can no longer be avoided by the operators and the industry as a whole. Decommissioning yields no return on investment and carries significant regulatory liabilities. The main objective of this paper is to provide an approach and mechanism for the estimation of emissions associated with decommissioning of Oil and Gas fields. The model uses gate to gate approach and considers field life from development phase up to asset end life. The model incorporates decommissioning processes which includes; well plugging, plant dismantling, wellhead, and pipeline dismantling, cutting and temporary fabrication, new manufacturing from raw material and recycling of metals. The results of the GHG emissions during decommissioning phase are 2.31x10-2 Kg CO2 Eq. per Mcf of the produced natural gas. Well plug and abandonment evolved to be the most GHG emitting activity with 84.7% of total field decommissioning operational emissions.

Keywords: LCA (life cycle analysis), gas field, decommissioning, emissions

Procedia PDF Downloads 185

Authors: Hassan Ali, Abdulrahman Hamid

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This paper discusses using of instruments to monitor deformation and settlement. Specifically, it concentrates on field instruments such as inclinometer and plate load test and their applications in the field. Inclinometer has been used effectively to monitor lateral earth movements and settlement in landslide areas, embankments and foundations. They are also used to monitor the deflection of retaining walls and piles under load. This paper is reviewing types of inclinometer systems, comparison between systems, applications, field accuracy and correction. The paper also will present a case study of using inclinometer to monitor the creep movements within the ancient landslide on The Washington Park Station. Furthermore, the application of deformation and settlement instruments in Saudi Arabia will be discussed in this manuscript.

Keywords: inclinometer, plate load test, backfills, sand, deformation and settlement

Procedia PDF Downloads 275

Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

Procedia PDF Downloads 79

Authors: Hongda Guo, Wenxia Sima

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Transformer oil is widely used in power systems because of its excellent insulation properties. The accurate measurement of electric field and space charge distribution in transformer oil under high voltage impulse has important theoretical and practical significance, but still remains challenging to date because of its low Kerr constant. In this study, the continuous electric field and space charge distribution over time between parallel-plate electrodes in high-voltage pulsed transformer oil based on the Kerr effect is directly measured using a linear array photoelectrical detector. Experimental results demonstrate the applicability and reliability of this method. This study provides a feasible approach to further study the space charge effects and breakdown mechanisms in transformer oil.

Keywords: electric field, Kerr, space charge, transformer oil

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Authors: Syed M. Jawwad Riaz

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There has been a lot of interest in exploring the thermodynamic properties at the horizon of a black hole geometry. Earlier, it has been shown, for different spacetimes, that the Einstein field equations at the horizon can be expressed as a first law of black hole thermodynamics. In this paper, considering r = constant slices, for the Kerr-Newman black hole, shown that the Einstein field equations for the induced 3-metric of the hypersurface is expressed in thermodynamic quantities under the virtual displacements of the hypersurfaces. As expected, it is found that the field equations of the induced metric corresponding to the horizon can only be written as a first law of black hole thermodynamics. It is to be mentioned here that the procedure adopted is much easier, to obtain such results, as here one has to essentially deal with (n - 1)-dimensional induced metric for an n-dimensional spacetime.

Keywords: black hole space-times, Einstein's field equation, foliation, hyper-surfaces

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

Procedia PDF Downloads 132

Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

Procedia PDF Downloads 427

Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: M.A.Bakry1, *, Aryn T. Shafeek1, +

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In this article, absolute Parallelism geometry is used to study the torsional gravitational field. And discovered the tetrad fields, torsion vector, and torsion scalar of Schwarzschild space. The new solution of the torsional gravitational field is a generalization of Schwarzschild in the context of general relativity. The results are applied to the planetary orbits.

Keywords: absolute parallelism geometry, tetrad fields, torsion vectors, torsion scalar

Procedia PDF Downloads 137

Authors: Anderson dos Santos Ananias, Matheus Yuji Shigueoka, Roberto Saverio Souza Costa

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Soil and water conservation can be conceptualized as a combination of management and use methods, which have the function of protecting them against deterioration induced by anthropogenic or natural factors. Thus, the objective of this research was to evaluate the rural extension work in soil conservation carried out at Sítio do Alto in Jaboticabal-SP, through the analysis of planimetric data (latitude and longitude coordinates) and altimetric differences of the empirically constructed terraces by the rural producer and with technical guidance from CATI (Coordination of Integral Technical Assistance). A data collection procedure was carried out in the field, with GPS L1/L2, before the construction of five (5) terraces technically level and after their construction. The results showed that the greatest differences were found on terrace one (1), with a maximum latitude difference of 57 meters, the longitude of 23 m, and altitude of 2 m. These results corroborate the observations in the field, in which the presence of a great erosion caused by the incorrect construction of terrace 1 was verified rainwater to the side of the rural property, where the largest erosion furrows with the beginning of gully formation were found.

Keywords: GPS, mechanical pratice, surface runoff, erosion

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Authors: R. Khare, R. V. Gelamo, M. A. More, D. J. Late, Chandra Sekhar Rout

Abstract:

Graphene emerges out as a promising material for various applications ranging from complementary integrated circuits to optically transparent electrode for displays and sensors. The excellent conductivity and atomic sharp edges of unique two-dimensional structure makes graphene a propitious field emitter. Graphene analogues of other 2D layered materials have emerged in material science and nanotechnology due to the enriched physics and novel enhanced properties they present. There are several advantages of using 2D nanomaterials in field emission based devices, including a thickness of only a few atomic layers, high aspect ratio (the ratio of lateral size to sheet thickness), excellent electrical properties, extraordinary mechanical strength and ease of synthesis. Furthermore, the presence of edges can enhance the tunneling probability for the electrons in layered nanomaterials similar to that seen in nanotubes. Here we report electron emission properties of multilayer graphene and effect of plasma (CO2, O2, Ar and N2) treatment. The plasma treated multilayer graphene shows an enhanced field emission behavior with a low turn on field of 0.18 V/μm and high emission current density of 1.89 mA/cm2 at an applied field of 0.35 V/μm. Further, we report the field emission studies of layered WS2/RGO and SnS2/RGO composites. The turn on field required to draw a field emission current density of 1μA/cm2 is found to be 3.5, 2.3 and 2 V/μm for WS2, RGO and the WS2/RGO composite respectively. The enhanced field emission behavior observed for the WS2/RGO nanocomposite is attributed to a high field enhancement factor of 2978, which is associated with the surface protrusions of the single-to-few layer thick sheets of the nanocomposite. The highest current density of ~800 µA/cm2 is drawn at an applied field of 4.1 V/μm from a few layers of the WS2/RGO nanocomposite. Furthermore, first-principles density functional calculations suggest that the enhanced field emission may also be due to an overlap of the electronic structures of WS2 and RGO, where graphene-like states are dumped in the region of the WS2 fundamental gap. Similarly, the turn on field required to draw an emission current density of 1µA/cm2 is significantly low (almost half the value) for the SnS2/RGO nanocomposite (2.65 V/µm) compared to pristine SnS2 (4.8 V/µm) nanosheets. The field enhancement factor β (~3200 for SnS2 and ~3700 for SnS2/RGO composite) was calculated from Fowler-Nordheim (FN) plots and indicates emission from the nanometric geometry of the emitter. The field emission current versus time plot shows overall good emission stability for the SnS2/RGO emitter. The DFT calculations reveal that the enhanced field emission properties of SnS2/RGO composites are because of a substantial lowering of work function of SnS2 when supported by graphene, which is in response to p-type doping of the graphene substrate. Graphene and 2D analogue materials emerge as a potential candidate for future field emission applications.

Keywords: graphene, layered material, field emission, plasma, doping

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Authors: N.Benachour, S. Chouchane, J. P. Chopart

Abstract:

The zinc-nickel deposition on stainless steel substrate was obtained in a chloride bath composed of ZnCl2 (1.8M), NiCl2.6H2O (1.1M), boric acid H3BO3 (1M) and NH4Cl (4M). One configuration was studied the amplitude or field B (0.5 et1T) is parallel to the surface of the working electrodes .the other share the study of various layer was carried out by XRD. The study of the effect of ammonium chloride in combination with the magnetohydrodynamic effect gave several deposits supposedly good physical properties.

Keywords: ammonium chloride, magnetic field, nickel-zinc alloys, co-deposition

Procedia PDF Downloads 268

Authors: Sonu Rana, Jyoti Verma, A. K. Gautam

Abstract:

In most developing countries like India, the majority of the population heavily relies on agriculture for their livelihood. The yield of agriculture is heavily dependent on uncertain weather conditions like a monsoon, soil fertility, availability of irrigation facilities and fertilizers as well as support from the government. The agricultural yield is quite less compared to the effort put in due to inefficient agricultural facilities and obsolete farming practices on the one hand and lack of knowledge on the other hand, and ultimately agricultural community does not prosper. It is therefore essential for the farmers to improve their harvest yield by the acquisition of related data such as soil condition, temperature, humidity, availability of irrigation facilities, availability of, manure, etc., and adopt smart farming techniques using modern agricultural equipment. Nowadays, using IOT technology in agriculture is the best solution to improve the yield with fewer efforts and economic costs. The primary focus of this work-related is IoT technology in the agriculture field. By using IoT all the parameters would be monitored by mounting sensors in an agriculture field held at different places, will collect real-time data, and could be transmitted by a transmitting device like an antenna. To improve the system, IoT will interact with other useful systems like Wireless Sensor Networks. IoT is exploring every aspect, so the radio frequency spectrum is getting crowded due to the increasing demand for wireless applications. Therefore, Federal Communications Commission is reallocating the spectrum for various wireless applications. An antenna is also an integral part of the newly designed IoT devices. The main aim is to propose a new antenna structure used for IoT agricultural applications and compatible with this new unlicensed frequency band. The main focus of this paper is to present work related to these technologies in the agriculture field. This also presented their challenges & benefits. It can help in understanding the job of data by using IoT and correspondence advancements in the horticulture division. This will help to motivate and educate the unskilled farmers to comprehend the best bits of knowledge given by the huge information investigation utilizing smart technology.

Keywords: smart agriculture, IoT, agriculture technology, data analytics, smart technology

Procedia PDF Downloads 111

Authors: H. Medoukali, B. Zegnini

Abstract:

Insulation techniques in high-voltage cables rely heavily on chemically synapsed polyethylene. The latter may contain manufacturing defects such as small cavities, for example. The presence of the cavity affects the distribution of the electric field at the level of the insulating layer; this change in the electric field is affected by the presence of different space charge densities within the insulating material. This study is carried out by performing simulations to determine the distribution of the electric field inside the insulator. The simulations are based on the creation of a two-dimensional model of a high-voltage cable of 154 kV using the COMSOL Multiphysics software. Each time we study the effect of changing the space charge density of on the electromechanical Constraints.

Keywords: COMSOL multiphysics, electric field, HVDC, microcavities, space charges, XLPE

Procedia PDF Downloads 127

Authors: K. S. Sruthi

Abstract:

Antennas are one of the most important parts of a communication chain. They are used for both communication and calibration purposes. New developments in probe technologies have enabled near-field probes with much larger bandwidth. The objective of this paper is to design, simulate and fabricate a dual polarized wide band inverted quad ridged shape horn antenna which can be used as measurement probe for near field measurements. The inverted quad-ridged horn antenna probe not only provides measurement in the much wider range but also provides dual-polarization measurement thus enabling antenna developers to measure UWB, UHF, VHF antennas more precisely and at lower cost. The antenna is designed to meet the characteristics such as high gain, light weight, linearly polarized with suppressed side lobes for near-field measurement applications. The proposed antenna is simulated with commercially available packages such as Ansoft HFSS. The antenna gives a moderate gain over operating range while delivering a wide bandwidth.

Keywords: near-field antenna measurement, inverted quad-ridge horn antenna, wideband Antennas, dual polarized antennas, ansoft HFSS

Procedia PDF Downloads 418

Authors: Abdoullah Nyassi, Golam Sarwar, Sarra Baldeh, Mamadou S. K. Jallow, Bai Lamin Dondeh, Isaac Osei, Grant A. Mackenzie

Abstract:

A randomized controlled trial is the "gold standard" for evaluating the efficacy of an intervention. Large-scale, cluster-randomized trials are expensive and difficult to conduct, though. To guarantee the validity and generalizability of findings, high-quality, dependable, and accurate data management systems are necessary. Robust data management systems are crucial for optimizing and validating the quality, accuracy, and dependability of trial data. Regarding the difficulties of data gathering in clinical trials in low-resource areas, there is a scarcity of literature on this subject, which may raise concerns. Effective data management systems and implementation goals should be part of trial procedures. Publicizing the creative clinical data management techniques used in clinical trials should boost public confidence in the study's conclusions and encourage further replication. In the ongoing pneumococcal vaccine schedule study in rural Gambia, this report details the development and deployment of multi-data management systems and methodologies. We implemented six different data management, synchronization, and reporting systems using Microsoft Access, RedCap, SQL, Visual Basic, Ruby, and ASP.NET. Additionally, data synchronization tools were developed to integrate data from these systems into the central server for reporting systems. Clinician, lab, and field data validation systems and methodologies are the main topics of this report. Our process development efforts across all domains were driven by the complexity of research project data collected in real-time data, online reporting, data synchronization, and ways for cleaning and verifying data. Consequently, we effectively used multi-data management systems, demonstrating the value of creative approaches in enhancing the consistency, accuracy, and reporting of trial data in a poor resource setting.

Keywords: data management, data collection, data cleaning, cluster-randomized trial

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Authors: Ali Ulvi Uzer

Abstract:

Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

Procedia PDF Downloads 452