Search results for: automatic impedance matching
567 Influence of Environmental Temperature on Dairy Herd Performance and Behaviour
Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh
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The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.Keywords: behavior, milk yield, temperature, precision technologies
Procedia PDF Downloads 109566 Functionality Based Composition of Web Services to Attain Maximum Quality of Service
Authors: M. Mohemmed Sha Mohamed Kunju, Abdalla A. Al-Ameen Abdurahman, T. Manesh Thankappan, A. Mohamed Mustaq Ahmed Hameed
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Web service composition is an effective approach to complete the web based tasks with desired quality. A single web service with limited functionality is inadequate to execute a specific task with series of action. So, it is very much required to combine multiple web services with different functionalities to reach the target. Also, it will become more and more challenging, when these services are from different providers with identical functionalities and varying QoS, so while composing the web services, the overall QoS is considered to be the major factor. Also, it is not true that the expected QoS is always attained when the task is completed. A single web service in the composed chain may affect the overall performance of the task. So care should be taken in different aspects such as functionality of the service, while composition. Dynamic and automatic service composition is one of the main option available. But to achieve the actual functionality of the task, quality of the individual web services are also important. Normally the QoS of the individual service can be evaluated by using the non-functional parameters such as response time, throughput, reliability, availability, etc. At the same time, the QoS is not needed to be at the same level for all the composed services. So this paper proposes a framework that allows composing the services in terms of QoS by setting the appropriate weight to the non-functional parameters of each individual web service involved in the task. Experimental results show that the importance given to the non-functional parameter while composition will definitely improve the performance of the web services.Keywords: composition, non-functional parameters, quality of service, web service
Procedia PDF Downloads 334565 Quantification of Effects of Structure-Soil-Structure Interactions on Urban Environment under Rayleigh Wave Loading
Authors: Neeraj Kumar, J. P. Narayan
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The effects of multiple Structure-Soil-Structure Interactions (SSSI) on the seismic wave-field is generally disregarded by earthquake engineers, particularly the surface waves which cause more damage to buildings. Closely built high rise buildings exchange substantial seismic energy with each other and act as a full-coupled dynamic system. In this paper, SSI effects on the building responses and the free field motion due to a small city consisting 25- homogenous buildings blocks of 10-storey are quantified. The rocking and translational behavior of building under Rayleigh wave loading is studied for different dimensions of the building. The obtained dynamic parameters of buildings revealed a reduction in building roof drift with an increase in number of buildings ahead of the considered building. The strain developed by vertical component of Rayleigh may cause tension in structural components of building. A matching of fundamental frequency of building for the horizontal component of Rayleigh wave with that for vertically incident SV-wave is obtained. Further, the fundamental frequency of building for the vertical vibration is approximately twice to that for horizontal vibration. The city insulation has caused a reduction of amplitude of Rayleigh wave up to 19.3% and 21.6% in the horizontal and vertical components, respectively just outside the city. Further, the insulating effect of city was very large at fundamental frequency of buildings for both the horizontal and vertical components. Therefore, it is recommended to consider the insulating effects of city falling in the path of Rayleigh wave propagation in seismic hazard assessment for an area.Keywords: structure-soil-structure interactions, Rayleigh wave propagation, finite difference simulation, dynamic response of buildings
Procedia PDF Downloads 217564 Autonomous Landing of UAV on Moving Platform: A Mathematical Approach
Authors: Mortez Alijani, Anas Osman
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Recently, the popularity of Unmanned aerial vehicles (UAVs) has skyrocketed amidst the unprecedented events and the global pandemic, as they play a key role in both the security and health sectors, through surveillance, taking test samples, transportation of crucial goods and spreading awareness among civilians. However, the process of designing and producing such aerial robots is suppressed by the internal and external constraints that pose serious challenges. Landing is one of the key operations during flight, especially, the autonomous landing of UAVs on a moving platform is a scientifically complex engineering problem. Typically having a successful automatic landing of UAV on a moving platform requires accurate localization of landing, fast trajectory planning, and robust control planning. To achieve these goals, the information about the autonomous landing process such as the intersection point, the position of platform/UAV and inclination angle are more necessary. In this study, the mathematical approach to this problem in the X-Y axis based on the inclination angle and position of UAV in the landing process have been presented. The experimental results depict the accurate position of the UAV, intersection between UAV and moving platform and inclination angle in the landing process, allowing prediction of the intersection point.Keywords: autonomous landing, inclination angle, unmanned aerial vehicles, moving platform, X-Y axis, intersection point
Procedia PDF Downloads 164563 SAMRA: Dataset in Al-Soudani Arabic Maghrebi Script for Recognition of Arabic Ancient Words Handwritten
Authors: Sidi Ahmed Maouloud, Cheikh Ba
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Much of West Africa’s cultural heritage is written in the Al-Soudani Arabic script, which was widely used in West Africa before the time of European colonization. This Al-Soudani Arabic script is an African version of the Maghrebi script, in particular, the Al-Mebssout script. However, the local African qualities were incorporated into the Al-Soudani script in a way that gave it a unique African diversity and character. Despite the existence of several Arabic datasets in Oriental script, allowing for the analysis, layout, and recognition of texts written in these calligraphies, many Arabic scripts and written traditions remain understudied. In this paper, we present a dataset of words from Al-Soudani calligraphy scripts. This dataset consists of 100 images selected from three different manuscripts written in Al-Soudani Arabic script by different copyists. The primary source for this database was the libraries of Boston University and Cambridge University. This dataset highlights the unique characteristics of the Al-Soudani Arabic script as well as the new challenges it presents in terms of automatic word recognition of Arabic manuscripts. An HTR system based on a hybrid ANN (CRNN-CTC) is also proposed to test this dataset. SAMRA is a dataset of annotated Arabic manuscript words in the Al-Soudani script that can help researchers automatically recognize and analyze manuscript words written in this script.Keywords: dataset, CRNN-CTC, handwritten words recognition, Al-Soudani Arabic script, HTR, manuscripts
Procedia PDF Downloads 131562 An Automatic Generating Unified Modelling Language Use Case Diagram and Test Cases Based on Classification Tree Method
Authors: Wassana Naiyapo, Atichat Sangtong
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The processes in software development by Object Oriented methodology have many stages those take time and high cost. The inconceivable error in system analysis process will affect to the design and the implementation process. The unexpected output causes the reason why we need to revise the previous process. The more rollback of each process takes more expense and delayed time. Therefore, the good test process from the early phase, the implemented software is efficient, reliable and also meet the user’s requirement. Unified Modelling Language (UML) is the tool which uses symbols to describe the work process in Object Oriented Analysis (OOA). This paper presents the approach for automatically generated UML use case diagram and test cases. UML use case diagram is generated from the event table and test cases are generated from use case specifications and Graphic User Interfaces (GUI). Test cases are derived from the Classification Tree Method (CTM) that classify data to a node present in the hierarchy structure. Moreover, this paper refers to the program that generates use case diagram and test cases. As the result, it can reduce work time and increase efficiency work.Keywords: classification tree method, test case, UML use case diagram, use case specification
Procedia PDF Downloads 163561 Multimedia Firearms Training System
Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel
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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.Keywords: firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics
Procedia PDF Downloads 224560 Sustainable Land Use Evaluation Based on Preservative Approach: Neighborhoods of Susa City
Authors: Somaye Khademi, Elahe Zoghi Hoseini, Mostafa Norouzi
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Determining the manner of land-use and the spatial structure of cities on the one hand, and the economic value of each piece of land, on the other hand, land-use planning is always considered as the main part of urban planning. In this regard, emphasizing the efficient use of land, the sustainable development approach has presented a new perspective on urban planning and consequently on its most important pillar, i.e. land-use planning. In order to evaluate urban land-use, it has been attempted in this paper to select the most significant indicators affecting urban land-use and matching sustainable development indicators. Due to the significance of preserving ancient monuments and the surroundings as one of the main pillars of achieving sustainability, in this research, sustainability indicators have been selected emphasizing the preservation of ancient monuments and historical observance of the city of Susa as one of the historical cities of Iran. It has also been attempted to integrate these criteria with other land-use sustainability indicators. For this purpose, Kernel Density Estimation (KDE) and the AHP model have been used for providing maps displaying spatial density and combining layers as well as providing final maps respectively. Moreover, the rating of sustainability will be studied in different districts of the city of Shush so as to evaluate the status of land sustainability in different parts of the city. The results of the study show that different neighborhoods of Shush do not have the same sustainability in land-use such that neighborhoods located in the eastern half of the city, i.e. the new neighborhoods, have a higher sustainability than those of the western half. It seems that the allocation of a high percentage of these areas to arid lands and historical areas is one of the main reasons for their sustainability.Keywords: city of Susa, historical heritage, land-use evaluation, urban sustainable development
Procedia PDF Downloads 380559 Exploratory Analysis of A Review of Nonexistence Polarity in Native Speech
Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori
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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing
Procedia PDF Downloads 133558 Abdominal Organ Segmentation in CT Images Based On Watershed Transform and Mosaic Image
Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid
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Accurate Liver, spleen and kidneys segmentation in abdominal CT images is one of the most important steps for computer aided abdominal organs pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for Liver, spleen and kidneys area extraction in abdominal CT images. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. The algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, multi-abdominal organ segmentation, mosaic image, the watershed algorithm
Procedia PDF Downloads 499557 The Correlation between Body Composition and Spinal Alignment in Healthy Young Adults
Authors: Ferruh Taspinar, Ismail Saracoglu, Emrah Afsar, Eda O. Okur, Gulce K. Seyyar, Gamze Kurt, Betul Taspinar
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Although it is thought that abdominal adiposity is one of the risk factor for postural deviation, such as increased lumbar lordosis, the body mass index is not sufficient to indicate effects of abdominal adiposity on spinal alignment and postural changes. The aim of this study was to investigate the correlation with detailed body composition and spine alignment in healthy young adults. This cross-sectional study was conducted with sixty seven healthy volunteers (37 men and 30 women) whose ages ranged between 19 and 27 years. All participants’ sagittal spinal curvatures of lumbar and thoracic region were measured via Spinal mouse® (Idiag, Fehraltorf, Switzerland). Also, body composition analysis (whole body fat ratio, whole body muscle ratio, abdominal fat ratio, and trunk muscle ratio) estimation by means of bioelectrical impedance was evaluated via Tanita Bc 418 Ma Segmental Body Composition Analyser (Tanita, Japan). Pearson’s correlation was used to analysis among the variables. The mean lumbar lordosis and thoracic kyphosis angles were 21.02°±9.39, 41.50°±7.97, respectively. Statistically analysis showed a significant positive correlation between whole body fat ratio and lumbar lordosis angle (r=0.28, p=0.02). Similarly, there was a positive correlation between abdominal fat ratio and lumbar lordosis angle (r=0.27, p=0.03). The thoracic kyphosis angle showed also positive correlation with whole body fat ratio (r=0.33, p=0.00) and abdominal fat ratio (r=0.40, p=0.01). The whole body muscle ratio showed negative correlation between lumbar lordosis (r=-0.28, p=0.02) and thoracic kyphosis angles (r=-0.33, p=0.00), although there was no statistically correlation between trunk muscle ratio, lumbar and thoracic curvatures (p>0.05). The study demonstrated that an increase of fat ratio and decrease of muscle ratio in abdominal region or whole body shifts the spinal alignment which may adversely affect the spinal loading. Therefore, whole body composition should be taken into account in spine rehabilitation.Keywords: body composition, lumbar lordosis, spinal alignment, thoracic kyphosis
Procedia PDF Downloads 387556 Design of Bacterial Pathogens Identification System Based on Scattering of Laser Beam Light and Classification of Binned Plots
Authors: Mubashir Hussain, Mu Lv, Xiaohan Dong, Zhiyang Li, Bin Liu, Nongyue He
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Detection and classification of microbes have a vast range of applications in biomedical engineering especially in detection, characterization, and quantification of bacterial contaminants. For identification of pathogens, different techniques are emerging in the field of biomedical engineering. Latest technology uses light scattering, capable of identifying different pathogens without any need for biochemical processing. Bacterial Pathogens Identification System (BPIS) which uses a laser beam, passes through the sample and light scatters off. An assembly of photodetectors surrounded by the sample at different angles to detect the scattering of light. The algorithm of the system consists of two parts: (a) Library files, and (b) Comparator. Library files contain data of known species of bacterial microbes in the form of binned plots, while comparator compares data of unknown sample with library files. Using collected data of unknown bacterial species, highest voltage values stored in the form of peaks and arranged in 3D histograms to find the frequency of occurrence. Resulting data compared with library files of known bacterial species. If sample data matching with any library file of known bacterial species, sample identified as a matched microbe. An experiment performed to identify three different bacteria particles: Enterococcus faecalis, Pseudomonas aeruginosa, and Escherichia coli. By applying algorithm using library files of given samples, results were compromising. This system is potentially applicable to several biomedical areas, especially those related to cell morphology.Keywords: microbial identification, laser scattering, peak identification, binned plots classification
Procedia PDF Downloads 150555 Offline Signature Verification Using Minutiae and Curvature Orientation
Authors: Khaled Nagaty, Heba Nagaty, Gerard McKee
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A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.Keywords: signature, ridge breaks, minutiae, orientation
Procedia PDF Downloads 148554 Evaluation of Chitin Filled Epoxy Coating for Corrosion Protection of Q235 Steel in Saline Environment
Authors: Innocent O. Arukalam, Emeka E. Oguzie
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Interest in the development of eco-friendly anti-corrosion coatings using bio-based renewable materials is gaining momentum recently. To this effect, chitin biopolymer, which is non-toxic, biodegradable, and inherently possesses anti-microbial property, was successfully synthesized from snail shells and used as a filler in the preparation of epoxy coating. The chitin particles were characterized with contact angle goniometer, scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectrophotometer, and X-ray diffractometer (XRD). The performance of the coatings was evaluated by immersion and electrochemical impedance spectroscopy (EIS) tests. Electronic structure properties of the coating ingredients and molecular level interaction of the corrodent and coated Q235 steel were appraised by quantum chemical computations (QCC) and molecular dynamics (MD) simulation techniques, respectively. The water contact angle (WCA) measurement of chitin particles was found to be 129.3o while that of chitin particles modified with amino trimethoxy silane (ATMS) was 149.6o, suggesting it is highly hydrophobic. Immersion and EIS analyses revealed that epoxy coating containing silane-modified chitin exhibited lowest water absorption and highest barrier as well as anti-corrosion performances. The QCC showed that quantum parameters for the coating containing silane-modified chitin are optimum and therefore corresponds to high corrosion protection. The high negative value of adsorption energies (Eads) for the coating containing silane-modified chitin indicates the coating molecules interacted and adsorbed strongly on the steel surface. The observed results have shown that silane-modified epoxy-chitin coating would perform satisfactorily for surface protection of metal structures in saline environment.Keywords: chitin, EIS, epoxy coating, hydrophobic, molecular dynamics simulation, quantum chemical computation
Procedia PDF Downloads 99553 Data Compression in Ultrasonic Network Communication via Sparse Signal Processing
Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi
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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.Keywords: data compression, ultrasonic communication, guided waves, FEM analysis
Procedia PDF Downloads 125552 Detection of Resistive Faults in Medium Voltage Overhead Feeders
Authors: Mubarak Suliman, Mohamed Hassan
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Detection of downed conductors occurring with high fault resistance (reaching kilo-ohms) has always been a challenge, especially in countries like Saudi Arabia, on which earth resistivity is very high in general (reaching more than 1000 Ω-meter). The new approaches for the detection of resistive and high impedance faults are based on the analysis of the fault current waveform. These methods are still under research and development, and they are currently lacking security and dependability. The other approach is communication-based solutions which depends on voltage measurement at the end of overhead line branches and communicate the measured signals to substation feeder relay or a central control center. However, such a detection method is costly and depends on the availability of communication medium and infrastructure. The main objective of this research is to utilize the available standard protection schemes to increase the probability of detection of downed conductors occurring with a low magnitude of fault currents and at the same time avoiding unwanted tripping in healthy conditions and feeders. By specifying the operating region of the faulty feeder, use of tripping curve for discrimination between faulty and healthy feeders, and with proper selection of core balance current transformer (CBCT) and voltage transformers with fewer measurement errors, it is possible to set the pick-up of sensitive earth fault current to minimum values of few amps (i.e., Pick-up Settings = 3 A or 4 A, …) for the detection of earth faults with fault resistance more than (1 - 2 kΩ) for 13.8kV overhead network and more than (3-4) kΩ fault resistance in 33kV overhead network. By implementation of the outcomes of this study, the probability of detection of downed conductors is increased by the utilization of existing schemes (i.e., Directional Sensitive Earth Fault Protection).Keywords: sensitive earth fault, zero sequence current, grounded system, resistive fault detection, healthy feeder
Procedia PDF Downloads 116551 Ultrasonic Spectroscopy of Polymer Based PVDF-TrFE Composites with CNT Fillers
Authors: J. Belovickis, V. Samulionis, J. Banys, M. V. Silibin, A. V. Solnyshkin, A. V. Sysa
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Ferroelectric polymers exhibit good flexibility, processability and low cost of production. Doping of ferroelectric polymers with nanofillers may modify its dielectric, elastic or piezoelectric properties. Carbon nanotubes are one of the ingredients that can improve the mechanical properties of polymer based composites. In this work, we report on both the ultrasonic and the dielectric properties of the copolymer polyvinylidene fluoride/tetrafluoroethylene (P(VDF-TrFE)) of the composition 70/30 mol% with various concentrations of carbon nanotubes (CNT). Experimental study of ultrasonic wave attenuation and velocity in these composites has been performed over wide temperature range (100 K – 410 K) using an ultrasonic automatic pulse-echo tecnique. The temperature dependences of ultrasonic velocity and attenuation showed anomalies attributed to the glass transition and paraelectric-ferroelectric phase transition. Our investigations showed mechanical losses to be dependent on the volume fraction of the CNTs within the composites. The existence of broad hysteresis of the ultrasonic wave attenuation and velocity within the nanocomposites is presented between cooling and heating cycles. By the means of dielectric spectroscopy, it is shown that the dielectric properties may be tuned by varying the volume fraction of the CNT fillers.Keywords: carbon nanotubes, polymer composites, PVDF-TrFE, ultrasonic spectroscopy
Procedia PDF Downloads 341550 Inhibition Effect of Natural Junipers Extract towards Steel Corrosion in HCl Solution
Authors: L. Bammou, M. Belkhaouda R. Salghi, L. Bazzi, B. Hammouti
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Steel and steel-based alloys of different grades steel are extensively used in numerous applications where acid solutions are widely applied such as industrial acid pickling, industrial acid cleaning and oil-well acidizing. The use of chemical inhibitors is one of the most practical methods for the protection against corrosion in acidic media. Most of the excellent acid inhibitors are organic compounds containing nitrogen, oxygen, phosphorus and sulphur. The use of non-toxic inhibitors called green or eco-friendly environmental inhibitors is one of the solutions possible to prevent the corrosion of the material. These advantages have incited us to draw a large part of program of our laboratory to examine natural substances as corrosion inhibitors such as: prickly pear seed oil, Argan oil, Argan extract, Fennel oil, Rosemary oil, Thymus oil, Lavender oil, Jojoba oil, Pennyroyal Mint oil, and Artemisia. In the present work, we investigate the corrosion inhibition of steel in 1 M HCl by junipers extract using weight loss, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) methods. The result obtained of junipers extract (JE) shows excellent inhibition properties for the corrosion of C38 steel in 1M HCl at 298K, and the inhibition efficiency increases with increasing of the JE concentration. The inhibitor efficiencies determined by weight loss, Tafel polarisation and EIS methods are in reasonable agreement. Based on the polarisation results, the investigated junipers extract can be classified as mixed inhibitor. The calculated structural parameters show increase of the obtained Rct values and decrease of the capacitance, Cdl, with JE concentration increase. It is suggested to attribute this to the increase of the thickness of the adsorption layer at steel surface. The adsorption model obeys to the Langmuir adsorption isotherm. The adsorption process is a spontaneous and exothermic process.Keywords: corrosion inhibition, steel, friendly inhibitors, Tafel polarisation
Procedia PDF Downloads 524549 Physics-Informed Convolutional Neural Networks for Reservoir Simulation
Authors: Jiangxia Han, Liang Xue, Keda Chen
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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation
Procedia PDF Downloads 147548 Studying the Possibility to Weld AA1100 Aluminum Alloy by Friction Stir Spot Welding
Authors: Ahmad K. Jassim, Raheem Kh. Al-Subar
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Friction stir welding is a modern and an environmentally friendly solid state joining process used to joint relatively lighter family of materials. Recently, friction stir spot welding has been used instead of resistance spot welding which has received considerable attention from the automotive industry. It is environmentally friendly process that eliminated heat and pollution. In this research, friction stir spot welding has been used to study the possibility to weld AA1100 aluminum alloy sheet with 3 mm thickness by overlapping the edges of sheet as lap joint. The process was done using a drilling machine instead of milling machine. Different tool rotational speeds of 760, 1065, 1445, and 2000 RPM have been applied with manual and automatic compression to study their effect on the quality of welded joints. Heat generation, pressure applied, and depth of tool penetration have been measured during the welding process. The result shows that there is a possibility to weld AA1100 sheets; however, there is some surface defect that happened due to insufficient condition of welding. Moreover, the relationship between rotational speed, pressure, heat generation and tool depth penetration was created.Keywords: friction, spot, stir, environmental, sustainable, AA1100 aluminum alloy
Procedia PDF Downloads 196547 ECG Based Reliable User Identification Using Deep Learning
Authors: R. N. Begum, Ambalika Sharma, G. K. Singh
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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio
Procedia PDF Downloads 164546 Automated Classification of Hypoxia from Fetal Heart Rate Using Advanced Data Models of Intrapartum Cardiotocography
Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw
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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.Keywords: cardiotocography, foetus, intrapartum, hypoxia
Procedia PDF Downloads 217545 Reducing Support Structures in Design for Additive Manufacturing: A Neural Networks Approach
Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson
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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks
Procedia PDF Downloads 255544 Enhanced Arabic Semantic Information Retrieval System Based on Arabic Text Classification
Authors: A. Elsehemy, M. Abdeen , T. Nazmy
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Since the appearance of the Semantic web, many semantic search techniques and models were proposed to exploit the information in ontology to enhance the traditional keyword-based search. Many advances were made in languages such as English, German, French and Spanish. However, other languages such as Arabic are not fully supported yet. In this paper we present a framework for ontology based information retrieval for Arabic language. Our system consists of four main modules, namely query parser, indexer, search and a ranking module. Our approach includes building a semantic index by linking ontology concepts to documents, including an annotation weight for each link, to be used in ranking the results. We also augmented the framework with an automatic document categorizer, which enhances the overall document ranking. We have built three Arabic domain ontologies: Sports, Economic and Politics as example for the Arabic language. We built a knowledge base that consists of 79 classes and more than 1456 instances. The system is evaluated using the precision and recall metrics. We have done many retrieval operations on a sample of 40,316 documents with a size 320 MB of pure text. The results show that the semantic search enhanced with text classification gives better performance results than the system without classification.Keywords: Arabic text classification, ontology based retrieval, Arabic semantic web, information retrieval, Arabic ontology
Procedia PDF Downloads 526543 Fight against Money Laundering with Optical Character Recognition
Authors: Saikiran Subbagari, Avinash Malladhi
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Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition
Procedia PDF Downloads 146542 e-Learning Security: A Distributed Incident Response Generator
Authors: Bel G Raggad
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An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection
Procedia PDF Downloads 438541 Acceleration-Based Motion Model for Visual Simultaneous Localization and Mapping
Authors: Daohong Yang, Xiang Zhang, Lei Li, Wanting Zhou
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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that obtains information in the environment for self-positioning and mapping. It is widely used in computer vision, robotics and other fields. Many visual SLAM systems, such as OBSLAM3, employ a constant-speed motion model that provides the initial pose of the current frame to improve the speed and accuracy of feature matching. However, in actual situations, the constant velocity motion model is often difficult to be satisfied, which may lead to a large deviation between the obtained initial pose and the real value, and may lead to errors in nonlinear optimization results. Therefore, this paper proposed a motion model based on acceleration, which can be applied on most SLAM systems. In order to better describe the acceleration of the camera pose, we decoupled the pose transformation matrix, and calculated the rotation matrix and the translation vector respectively, where the rotation matrix is represented by rotation vector. We assume that, in a short period of time, the changes of rotating angular velocity and translation vector remain the same. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of constant velocity model was analyzed theoretically. Finally, we applied our proposed approach to the ORBSLAM3 system and evaluated two sets of sequences on the TUM dataset. The results showed that our proposed method had a more accurate initial pose estimation and the accuracy of ORBSLAM3 system is improved by 6.61% and 6.46% respectively on the two test sequences.Keywords: error estimation, constant acceleration motion model, pose estimation, visual SLAM
Procedia PDF Downloads 95540 A New Intelligent, Dynamic and Real Time Management System of Sewerage
Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem
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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.Keywords: automation, optimization, paradigm, RTC
Procedia PDF Downloads 301539 Optimizing Fire Suppression Time in Buildings by Forming a Fire Feedback Loop
Authors: Zhdanova A. O., Volkov R. S., Kuznetsov G. V., Strizhak P. A.
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Fires in different types of facilities are a serious problem worldwide.It is still an unaccomplished science and technology objective to establish the minimum number and type of sensors in automatic systems of compartment fire suppression which would turn the fire-extinguishing agent spraying on and off in real time depending on the state of the fire, minimize the amount of agent applied, delay time in fire suppression and system response, as well as the time of combustion suppression. Based on the results of experimental studies, the conclusion was made that it is reasonable to use a gas analysis system and heat sensors (in the event of their prior activation) to determine the effectiveness of fire suppression (fire-extinguishing composition interacts with the fire). Thus, the concentration of CO in the interaction of the firefighting liquid with the fire increases to 0.7–1.2%, which indicates a slowdown in the flame combustion, and heat sensors stop responding at a gas medium temperature below 80 ºC, which shows a gradual decrease in the heat release from the fire. The evidence from this study suggests that the information received from the video recording equipment (video camera) should be used in real time as an additional parameter confirming fire suppression. Research was supported by Russian Science Foundation (project No 21-19-00009, https://rscf.ru/en/project/21-19-00009/).Keywords: compartment fires, fire suppression, continuous control of fire behavior, feedback systems
Procedia PDF Downloads 130538 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification
Authors: Bing Li, Zhi Li, Yilong Yang
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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery
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