Search results for: Random Field Ising Model
23749 Prediction of Oil Recovery Factor Using Artificial Neural Network
Authors: O. P. Oladipo, O. A. Falode
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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger
Procedia PDF Downloads 44123748 Oil Reservoirs Bifurcation Analysis in the Democratic Republic of Congo: Fractal Characterization Approach of Makelekese MS-25 Field
Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, D. Nahum Kabeya
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In this paper the bifurcation analysis of oilfield in Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km2, a central basin with an area of 800,000 km2, the western branch of the East African Rift in which there are 50,000 km2. The fractal characterization of complex hydro-dynamic fractures in oilfield is developed to facilitate oil production process based on reservoirs bifurcation model.Keywords: reservoir bifurcation, fractal characterisation, permeability, conductivity, skin effect
Procedia PDF Downloads 19923747 Study Case of Spacecraft Instruments in Structural Modelling with Nastran-Patran
Authors: Francisco Borja de Lara, Ali Ravanbakhsh, Robert F. Wimmer-Schweingruber, Lars Seimetz, Fermín Navarro
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The intense structural loads during the launch of a spacecraft represent a challenge for the space structure designers because enough resistance has to be achieved while maintaining at the same time the mass and volume within the allowable margins of the mission requirements and inside the limits of the budget project. In this conference, we present the structural analysis of the Lunar Lander Neutron Dosimetry (LND) experiment on the Chang'E4 mission, the first probe to land on the moon’s far side included in the Chinese’ Moon Exploration Program by the Chinese National Space Administration. To this target, the software Nastran/Patran has been used: a structural model in Patran and a structural analysis through Nastran have been realized. Next, the results obtained are used both for the optimization process of the spacecraft structure, and as input parameters for the model structural test campaign. In this way, the feasibility of the lunar instrument structure is demonstrated in terms of the modal modes, stresses, and random vibration and a better understanding of the structural tests design is provided by our results.Keywords: Chang’E4, Chinese national space administration, lunar lander neutron dosimetry, nastran-patran, structural analysis
Procedia PDF Downloads 52923746 Model-Based Field Extraction from Different Class of Administrative Documents
Authors: Jinen Daghrir, Anis Kricha, Karim Kalti
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The amount of incoming administrative documents is massive and manually processing these documents is a costly task especially on the timescale. In fact, this problem has led an important amount of research and development in the context of automatically extracting fields from administrative documents, in order to reduce the charges and to increase the citizen satisfaction in administrations. In this matter, we introduce an administrative document understanding system. Given a document in which a user has to select fields that have to be retrieved from a document class, a document model is automatically built. A document model is represented by an attributed relational graph (ARG) where nodes represent fields to extract, and edges represent the relation between them. Both of vertices and edges are attached with some feature vectors. When another document arrives to the system, the layout objects are extracted and an ARG is generated. The fields extraction is translated into a problem of matching two ARGs which relies mainly on the comparison of the spatial relationships between layout objects. Experimental results yield accuracy rates from 75% to 100% tested on eight document classes. Our proposed method has a good performance knowing that the document model is constructed using only one single document.Keywords: administrative document understanding, logical labelling, logical layout analysis, fields extraction from administrative documents
Procedia PDF Downloads 21323745 Field Oriented Control of Electrical Motor for Efficiency Improvement of Aerial Vehicle
Authors: Francois Defay
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Uses of Unmanned aerial vehicle (UAV) are increasing for many applicative cases. Long endurance UAVs are required for inspection or transportation in some deserted places. The global optimization of the efficiency is the aim of the works in ISAE-SUPAERO. From the propulsive part until the motor control, the global optimization can increase significantly the global efficiency. This paper deals with the global improvement of the efficiency of the electrical propulsion for the aerial vehicle. The application case of study is a small airplane of 2kg. A global modelization is presented in order to validate the electrical engine in a complete simulation from aerodynamics to battery. The classical control of the synchronous permanent drive is compared to the field-oriented control which is not yet applied for UAVs. The experimental results presented show an increase of more than 10 percent of the efficiency. A complete modelization and simulation based on Matlab/ Simulink are presented in this paper and compared to the experimental study. Finally this paper presents solutions to increase the endurance of the electrical aerial vehicle and provide models to optimize the global consumption for a specific mission. The next step is to use this model and the control to work with distributed propulsion which is the future for small distance plane.Keywords: electrical propulsion, endurance, field-oriented control, UAV
Procedia PDF Downloads 23723744 Ophthalmic Hashing Based Supervision of Glaucoma and Corneal Disorders Imposed on Deep Graphical Model
Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu
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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing
Procedia PDF Downloads 25123743 Developing a Maturity Model of Digital Twin Application for Infrastructure Asset Management
Authors: Qingqing Feng, S. Thomas Ng, Frank J. Xu, Jiduo Xing
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Faced with unprecedented challenges including aging assets, lack of maintenance budget, overtaxed and inefficient usage, and outcry for better service quality from the society, today’s infrastructure systems has become the main focus of many metropolises to pursue sustainable urban development and improve resilience. Digital twin, being one of the most innovative enabling technologies nowadays, may open up new ways for tackling various infrastructure asset management (IAM) problems. Digital twin application for IAM, as its name indicated, represents an evolving digital model of intended infrastructure that possesses functions including real-time monitoring; what-if events simulation; and scheduling, maintenance, and management optimization based on technologies like IoT, big data and AI. Up to now, there are already vast quantities of global initiatives of digital twin applications like 'Virtual Singapore' and 'Digital Built Britain'. With digital twin technology permeating the IAM field progressively, it is necessary to consider the maturity of the application and how those institutional or industrial digital twin application processes will evolve in future. In order to deal with the gap of lacking such kind of benchmark, a draft maturity model is developed for digital twin application in the IAM field. Firstly, an overview of current smart cities maturity models is given, based on which the draft Maturity Model of Digital Twin Application for Infrastructure Asset Management (MM-DTIAM) is developed for multi-stakeholders to evaluate and derive informed decision. The process of development follows a systematic approach with four major procedures, namely scoping, designing, populating and testing. Through in-depth literature review, interview and focus group meeting, the key domain areas are populated, defined and iteratively tuned. Finally, the case study of several digital twin projects is conducted for self-verification. The findings of the research reveal that: (i) the developed maturity model outlines five maturing levels leading to an optimised digital twin application from the aspects of strategic intent, data, technology, governance, and stakeholders’ engagement; (ii) based on the case study, levels 1 to 3 are already partially implemented in some initiatives while level 4 is on the way; and (iii) more practices are still needed to refine the draft to be mutually exclusive and collectively exhaustive in key domain areas.Keywords: digital twin, infrastructure asset management, maturity model, smart city
Procedia PDF Downloads 15723742 Prediction Model of Body Mass Index of Young Adult Students of Public Health Faculty of University of Indonesia
Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono
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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length
Procedia PDF Downloads 21423741 Translation Quality Assessment in Fansubbed English-Chinese Swearwords: A Corpus-Based Study of the Big Bang Theory
Authors: Qihang Jiang
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Fansubbing, the combination of fan and subtitling, is one of the main branches of Audiovisual Translation (AVT) having kindled more and more interest of researchers into the AVT field in recent decades. In particular, the quality of so-called non-professional translation seems questionable due to the non-transparent qualification of subtitlers in a huge community network. This paper attempts to figure out how YYeTs aka 'ZiMuZu', the largest fansubbing group in China, translates swearwords from English to Chinese for its fans of the prevalent American sitcom The Big Bang Theory, taking cultural, social and political elements into account in the context of China. By building a bilingual corpus containing both the source and target texts, this paper found that most of the original swearwords were translated in a toned-down manner, probably due to Chinese audiences’ cultural and social network features as well as the strict censorship under the Chinese government. Additionally, House (2015)’s newly revised model of Translation Quality Assessment (TQA) was applied and examined. Results revealed that most of the subtitled swearwords achieved their pragmatic functions and exerted a communicative effect for audiences. In conclusion, this paper enriches the empirical research concerning House’s new TQA model, gives a full picture of the subtitling of swearwords in AVT field and provides a practical guide for the practitioners in their career of subtitling.Keywords: corpus-based approach, fansubbing, pragmatic functions, swearwords, translation quality assessment
Procedia PDF Downloads 14323740 Heart Ailment Prediction Using Machine Learning Methods
Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula
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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting
Procedia PDF Downloads 5123739 A Theoretical Hypothesis on Ferris Wheel Model of University Social Responsibility
Authors: Le Kang
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According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structure to afford social responsibilities; that makes the organization could obtain a synergistic effect to achieve more extensive interests of stakeholders and wider social responsibilities.Keywords: USR, achievement model, ferris wheel model, social responsibilities
Procedia PDF Downloads 72523738 Unsupervised Learning and Similarity Comparison of Water Mass Characteristics with Gaussian Mixture Model for Visualizing Ocean Data
Authors: Jian-Heng Wu, Bor-Shen Lin
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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.Keywords: water mass, Gaussian mixture model, data visualization, system framework
Procedia PDF Downloads 14523737 Model Predictive Control of Three Phase Inverter for PV Systems
Authors: Irtaza M. Syed, Kaamran Raahemifar
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This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a three leg voltage source inverter (VSI). Operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation and results show simplicity and accuracy, as well as reliability of the model.Keywords: model predictive control, three phase voltage source inverter, PV system, Matlab/simulink
Procedia PDF Downloads 59623736 Flow Field Analysis of a Liquid Ejector Pump Using Embedded Large Eddy Simulation Methodology
Authors: Qasim Zaheer, Jehanzeb Masud
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The understanding of entrainment and mixing phenomenon in the ejector pump is of pivotal importance for designing and performance estimation. In this paper, the existence of turbulent vortical structures due to Kelvin-Helmholtz instability at the free surface between the motive and the entrained fluids streams are simulated using Embedded LES methodology. The efficacy of Embedded LES for simulation of complex flow field of ejector pump is evaluated using ANSYS Fluent®. The enhanced mixing and entrainment process due to breaking down of larger eddies into smaller ones as a consequence of Vortex Stretching phenomenon is captured in this study. Moreover, the flow field characteristics of ejector pump like pressure velocity fields and mass flow rates are analyzed and validated against the experimental results.Keywords: Kelvin Helmholtz instability, embedded LES, complex flow field, ejector pump
Procedia PDF Downloads 29723735 Electrohydrodynamic Study of Microwave Plasma PECVD Reactor
Authors: Keltoum Bouherine, Olivier Leroy
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The present work is dedicated to study a three–dimensional (3D) self-consistent fluid simulation of microwave discharges of argon plasma in PECVD reactor. The model solves the Maxwell’s equations, continuity equations for charged species and the electron energy balance equation, coupled with Poisson’s equation, and Navier-Stokes equations by finite element method, using COMSOL Multiphysics software. In this study, the simulations yield the profiles of plasma components as well as the charge densities and electron temperature, the electric field, the gas velocity, and gas temperature. The results show that the microwave plasma reactor is outside of local thermodynamic equilibrium.The present work is dedicated to study a three–dimensional (3D) self-consistent fluid simulation of microwave discharges of argon plasma in PECVD reactor. The model solves the Maxwell’s equations, continuity equations for charged species and the electron energy balance equation, coupled with Poisson’s equation, and Navier-Stokes equations by finite element method, using COMSOL Multiphysics software. In this study, the simulations yield the profiles of plasma components as well as the charge densities and electron temperature, the electric field, the gas velocity, and gas temperature. The results show that the microwave plasma reactor is outside of local thermodynamic equilibrium.Keywords: electron density, electric field, microwave plasma reactor, gas velocity, non-equilibrium plasma
Procedia PDF Downloads 33123734 Use of Giant Magneto Resistance Sensors to Detect Micron to Submicron Biologic Objects
Authors: Manon Giraud, Francois-Damien Delapierre, Guenaelle Jasmin-Lebras, Cecile Feraudet-Tarisse, Stephanie Simon, Claude Fermon
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Early diagnosis or detection of harmful substances at low level is a growing field of high interest. The ideal test should be cheap, easy to use, quick, reliable, specific, and with very low detection limit. Combining the high specificity of antibodies-functionalized magnetic beads used to immune-capture biologic objects and the high sensitivity of a GMR-based sensors, it is possible to even detect these biologic objects one by one, such as a cancerous cell, a bacteria or a disease biomarker. The simplicity of the detection process makes its use possible even for untrained staff. Giant Magneto Resistance (GMR) is a recently discovered effect consisting in the electrical resistance modification of some conductive layers when exposed to a magnetic field. This effect allows the detection of very low variations of magnetic field (typically a few tens of nanoTesla). Magnetic nanobeads coated with antibodies targeting the analytes are mixed with a biological sample (blood, saliva) and incubated for 45 min. Then the mixture is injected in a very simple microfluidic chip and circulates above a GMR sensor that detects changes in the surrounding magnetic field. Magnetic particles do not create a field sufficient to be detected. Therefore, only the biological objects surrounded by several antibodies-functionalized magnetic beads (that have been captured by the complementary antigens) are detected when they move above the sensor. Proof of concept has been carried out on NS1 mouse cancerous cells diluted in PBS which have been bonded to magnetic 200nm particles. Signals were detected in cells-containing samples while none were recorded for negative controls. Binary response was hence assessed for this first biological model. The precise quantification of the analytes and its detection in highly diluted solution is the step now in progress.Keywords: early diagnosis, giant magnetoresistance, lab-on-a-chip, submicron particle
Procedia PDF Downloads 24823733 Assessment of Yield and Water Use Efficiency of Soybean under Deficit Irrigation
Authors: Meysam Abedinpour
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Water limitation is the main challenge for crop production in a semi-arid environment. Deficit irrigation is a strategy that allows a crop to sustain some degree of water deficit in order to reduce costs and potentially increase income. For this goal, a field experimental carried out at Asrieh fields of Gorgan city in the north of Iran, during summer season 2011. The treatments imposed were different irrigation water regimes (i.e. W1:70, W2:80, W3:90, and W4:100) percent of field capacity (FC). The results showed that there was Significant difference between the yield and (WUE) under different levels of irrigation, excepting of soil moisture content at field capacity (W4) and 90% of field capacity (W3) on yield and water use efficiency (WUE). The seasonal irrigation water applied were (i.e. 375, 338, 300, and 263 mm ha-1) under different irrigation water treatments (100, 90, 80, 80 and 70%) of FC, respectively. Grain yield productions under treatments were 4180, 3955, 3640, and 3355 (kg ha-1) respectively. Furthermore, the results showed that water use efficiency (WUE) at different treatments were 7.67, 7.79, 7.74, and 7.75 Kg mm ha-1 for (100, 90, 80, and 70) per cent of field capacity, therefore the 90 % of FC treatment (W3) is recommended for Soybean irrigation for water saving. Furthermore, the result showed that the treatment of 90 % of filed capacity (W3) seemed to be better adapted to product a high crop yield with acceptable yield coupling with water use efficiency in Golestan province.Keywords: deficit irrigation, water use efficiency, yield, soybean
Procedia PDF Downloads 46923732 Field Saturation Flow Measurement Using Dynamic Passenger Car Unit under Mixed Traffic Condition
Authors: Ramesh Chandra Majhi
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Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.Keywords: optimization, passenger car unit, saturation flow, signalized intersection
Procedia PDF Downloads 32723731 Oil Reservoirs Bifurcation Analysis in the Democratic Republic of Congo: Fractal Characterization Approach of Makelekese MS-25 Field
Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, Dieudonne Nahum Kabeya
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In this paper, the bifurcation analysis of oilfields in the Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in the Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km², a central basin with an area of 800,000 km², the western branch of the East African Rift in which there are 50,000 km². The fractal characterization of complex hydro-dynamic fractures in oilfields is developed to facilitate the oil production process based on the reservoirs bifurcation model.Keywords: reservoir bifurcation, fractal characterization, permeability, conductivity, skin effect
Procedia PDF Downloads 13123730 Research of the Rotation Magnetic Field Current Driven Effect on Pulsed Plasmoid Acceleration of Electric Propulsion
Authors: X. F. Sun, X. D. Wen, L. J. Liu, C. C. Wu, Y. H. Jia
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The field reversed closed magnetic field configuration plasmoid has a potential for large thrust and high power propulsion missions such as deep space exploration due to its high plasma density and larger azimuthal current, which will be a most competitive program for the next generation electric propulsion technology. Moreover, without the electrodes, it also has a long lifetime. Thus, the research on this electric propulsion technology is quite necessary. The plasmoid will be formatted and accelerated by applying a rotation magnetic field (RMF) method. And, the essence of this technology lies on the generation of the azimuthal electron currents driven by RMF. Therefore, the effect of RMF current on the plasmoid acceleration efficiency is a concerned problem. In the paper, the influences of the penetration process of RMF in plasma, the relations of frequency and amplitude of input RF power with current strength and the RMF antenna configuration on the plasmoid acceleration efficiency will be given by a two-fluid numerical simulation method. The results show that the radio-frequency and input power have remarkable influence on the formation and acceleration of plasmoid. These results will provide useful advice for the development, and optimized designing of field reversed configuration plasmoid thruster.Keywords: rotation magnetic field, current driven, plasma penetration, electric propulsion
Procedia PDF Downloads 11623729 Current Characteristic of Water Electrolysis to Produce Hydrogen, Alkaline, and Acid Water
Authors: Ekki Kurniawan, Yusuf Nur Jayanto, Erna Sugesti, Efri Suhartono, Agus Ganda Permana, Jaspar Hasudungan, Jangkung Raharjo, Rintis Manfaati
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The purpose of this research is to study the current characteristic of the electrolysis of mineral water to produce hydrogen, alkaline water, and acid water. Alkaline and hydrogen water are believed to have health benefits. Alkaline water containing hydrogen can be an anti-oxidant that captures free radicals, which will increase the immune system. In Indonesia, there are two existing types of alkaline water producing equipment, but the installation is complicated, and the price is relatively expensive. The electrolysis process is slow (6-8 hours) since they are locally made using 311 VDC full bridge rectifier power supply. This paper intends to discuss how to make hydrogen and alkaline water by a simple portable mineral water ionizer. This is an electrolysis device that is easy to carry and able to separate ions of mineral water into acidic and alkaline water. With an electric field, positive ions will be attracted to the cathode, while negative ions will be attracted to the anode. The circuit equivalent can be depicted as RLC transient ciruit. The diode component ensures that the electrolytic current is direct current. Switch S divides the switching times t1, t2, and t3. In the first stage up to t1, the electrolytic current increases exponentially, as does the inductor charging current (L). The molecules in drinking water experience magnetic properties. The direction of the dipole ions, which are random in origin, will regularly flare with the direction of the electric field. In the second stage up to t2, the electrolytic current decreases exponentially, just like the charging current of a capacitor (C). In the 3rd stage, start t3 until it tends to be constant, as is the case with the current flowing through the resistor (R).Keywords: current electrolysis, mineral water, ions, alkaline and acid waters, inductor, capacitor, resistor
Procedia PDF Downloads 11323728 A Chinese Nested Named Entity Recognition Model Based on Lexical Features
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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm
Procedia PDF Downloads 12823727 Hedonic Price Analysis of Consumer Preference for Musa spp in Northern Nigeria
Authors: Yakubu Suleiman, S. A. Musa
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The research was conducted to determine the physical characteristics of banana fruits that influenced consumer preferences for the fruit in Northern Nigeria. Socio-economic characteristics of the respondents were also identified. Simple descriptive statistics and Hedonic prices model were used to analyze the data collected for socio-economic and consumer preference respectively with the aid of 1000 structured questionnaires. The result revealed the value of R2 to be 0.633, meaning that, 63.3% of the variation in the banana price was brought about by the explanatory variables included in the model and the variables are: colour, size, degree of ripeness, softness, surface blemish, cleanliness of the fruits, weight, length, and cluster size of fruits. However, the remaining 36.7% could be attributed to the error term or random disturbance in the model. It could also be seen from the calculated result that the intercept was 1886.5 and was statistically significant (P < 0.01), meaning that about N1886.5 worth of banana fruits could be bought by consumers without considering the variables of banana included in the model. Moreover, consumers showed that they have significant preference for colours, size, degree of ripeness, softness, weight, length and cluster size of banana fruits and they were tested to be significant at either P < 0.01, P < 0.05, and P < 0.1 . Moreover, the result also shows that consumers did not show significance preferences to surface blemish, cleanliness and variety of the banana fruit as all of them showed non-significance level with negative signs. Based on the findings of the research, it is hereby recommended that plant breeders and research institutes should concentrate on the production of banana fruits that have those physical characteristics that were found to be statistically significance like cluster size, degree of ripeness,’ softness, length, size, and skin colour.Keywords: analysis, consumers, preference, variables
Procedia PDF Downloads 34323726 Nanoscale Photo-Orientation of Azo-Dyes in Glassy Environments Using Polarized Optical Near-Field
Authors: S. S. Kharintsev, E. A. Chernykh, S. K. Saikin, A. I. Fishman, S. G. Kazarian
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Recent advances in improving information storage performance are inseparably linked with circumvention of fundamental constraints such as the supermagnetic limit in heat assisted magnetic recording, charge loss tolerance in solid-state memory and the Abbe’s diffraction limit in optical storage. A substantial breakthrough in the development of nonvolatile storage devices with dimensional scaling has been achieved due to phase-change chalcogenide memory, which nowadays, meets the market needs to the greatest advantage. A further progress is aimed at the development of versatile nonvolatile high-speed memory combining potentials of random access memory and archive storage. The well-established properties of light at the nanoscale empower us to use them for recording optical information with ultrahigh density scaled down to a single molecule, which is the size of a pit. Indeed, diffraction-limited optics is able to record as much information as ~1 Gb/in2. Nonlinear optical effects, for example, two-photon fluorescence recording, allows one to decrease the extent of the pit even more, which results in the recording density up to ~100 Gb/in2. Going beyond the diffraction limit, due to the sub-wavelength confinement of light, pushes the pit size down to a single chromophore, which is, on average, of ~1 nm in length. Thus, the memory capacity can be increased up to the theoretical limit of 1 Pb/in2. Moreover, the field confinement provides faster recording and readout operations due to the enhanced light-matter interaction. This, in turn, leads to the miniaturization of optical devices and the decrease of energy supply down to ~1 μW/cm². Intrinsic features of light such as multimode, mixed polarization and angular momentum in addition to the underlying optical and holographic tools for writing/reading, enriches the storage and encryption of optical information. In particular, the finite extent of the near-field penetration, falling into a range of 50-100 nm, gives the possibility to perform 3D volume (layer-to-layer) recording/readout of optical information. In this study, we demonstrate a comprehensive evidence of isotropic-to-homeotropic phase transition of the azobenzene-functionalized polymer thin film exposed to light and dc electric field using near-field optical microscopy and scanning capacitance microscopy. We unravel a near-field Raman dichroism of a sub-10 nm thick epoxy-based side-chain azo-polymer films with polarization-controlled tip-enhanced Raman scattering. In our study, orientation of azo-chromophores is controlled with a bias voltage gold tip rather than light polarization. Isotropic in-plane and homeotropic out-of-plane arrangement of azo-chromophores in glassy environment can be distinguished with transverse and longitudinal optical near-fields. We demonstrate that both phases are unambiguously visualized by 2D mapping their local dielectric properties with scanning capacity microscopy. The stability of the polar homeotropic phase is strongly sensitive to the thickness of the thin film. We make an analysis of α-transition of the azo-polymer by detecting a temperature-dependent phase jump of an AFM cantilever when passing through the glass temperature. Overall, we anticipate further improvements in optical storage performance, which approaches to a single molecule level.Keywords: optical memory, azo-dye, near-field, tip-enhanced Raman scattering
Procedia PDF Downloads 17723725 Model Observability – A Monitoring Solution for Machine Learning Models
Authors: Amreth Chandrasehar
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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.Keywords: model observability, monitoring, drift detection, ML observability platform
Procedia PDF Downloads 11223724 The Effect of Bottom Shape and Baffle Length on the Flow Field in Stirred Tanks in Turbulent and Transitional Flow
Authors: Jie Dong, Binjie Hu, Andrzej W Pacek, Xiaogang Yang, Nicholas J. Miles
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The effect of the shape of the vessel bottom and the length of baffles on the velocity distributions in a turbulent and in a transitional flow has been simulated. The turbulent flow was simulated using standard k-ε model and simulation was verified using LES whereas transitional flow was simulated using only LES. It has been found that both the shape of tank bottom and the baffles’ length has significant effect on the flow pattern and velocity distribution below the impeller. In the dished bottom tank with baffles reaching the edge of the dish, the large rotating volume of liquid was formed below the impeller. Liquid in this rotating region was not fully mixing. A dead zone was formed here. The size and the intensity of circulation within this zone calculated by k-ε model and LES were practically identical what reinforces the accuracy of the numerical simulations. Both types of simulations also show that employing full-length baffles can reduce the size of dead zone formed below the impeller. The LES was also used to simulate the velocity distribution below the impeller in transitional flow and it has been found that secondary circulation loops were formed near the tank bottom in all investigated geometries. However, in this case the length of baffles has smaller effect on the volume of rotating liquid than in the turbulent flow.Keywords: baffles length, dished bottom, dead zone, flow field
Procedia PDF Downloads 29523723 A Global Business Network Built on Hive: Two Use Cases: Buying and Selling of Products and Services and Carrying Out of Social Impact Projects
Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran
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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.Keywords: Hive, business, network, blockchain
Procedia PDF Downloads 6823722 An Investigation of Customer Relationship Management of Tourism
Authors: Wanida Suwunniponth
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This research paper aimed to developing a causal relationship model of success factors of customer relationship management of tourism in Thailand and to investigating relationships among the potential factors that facilitate the success of customer relationship management (CRM). The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. The questionnaire was used in collecting the data from 250 management staff in the hotels located within Bangkok area. Sampling techniques used in this research included cluster sampling according to the service quality and simple random sampling. The data input was analyzed by use of descriptive analysis and System Equation Model (SEM). The research findings demonstrated important factors accentuated by most respondents towards the success of CRM, which were organization, people, information technology and the process of CRM. Moreover, the customer relationship management of tourism business in Thailand was found to be successful at a very significant level. The hypothesis testing showed that the hypothesis was accepted, as the factors concerning with organization, people and information technology played an influence on the process and the success of customer relationship management, whereas the process of customer relationship management factor manipulated its success. The findings suggested that tourism business in Thailand with the implementation of customer relationship management should opt in improvement approach in terms of managerial structure, corporate culture building with customer- centralized approach accentuated, and investment of information technology and customer analysis, in order to capacitate higher efficiency of customer relationship management process that would result in customer satisfaction and retention of service.Keywords: customer relationship management, casual relationship model, tourism, Thailand
Procedia PDF Downloads 33023721 The Impact of Cognitive Load on Deceit Detection and Memory Recall in Children’s Interviews: A Meta-Analysis
Authors: Sevilay Çankaya
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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis
Procedia PDF Downloads 5523720 The Systems Theoretic Accident Model and Process (Stamp) as the New Trend to Promote Safety Culture in Construction
Authors: Natalia Ortega
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Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety
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