Search results for: restructuringdigital factory model
11635 Numerical Simulation of Liquid Nitrogen Spray Equipment for Space Environmental Simulation Facility
Authors: He Chao, Zhang Lei, Liu Ran, Li Ang
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Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keep the shrouds in the temperature range from -150℃ to +150℃. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.Keywords: space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent
Procedia PDF Downloads 40111634 CO2 Adsorption on the Activated Klaten-Indonesian Natural Zeolite in a Packed Bed Adsorber
Authors: Sang Kompiang Wirawan, Chandra Purnomo
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Carbon dioxide (CO2) adsorption on the activated Klaten-Indonesian natural zeolite (AKINZ) in a packed bed adsorber has been studied. Experiment works consisted of acid activation and adsorption experiments. The natural zeolite sample was activated using 0.3 M HCl at the temperature of 353 K. In the adsorption experiments the feed gas concentrations were 40 and 80 % CO2 in helium within various temperatures of 303; 323 and 373 K. The experiments were conducted by using transient step change adsorption and 20 % Ar/He tracer experiment was conducted to measure dispersion and time lag effect of the packed bed system. A mathematical model of CO2 adsorption had been set up by assuming plug flow;isothermal;isobaric and no gas film mass transport resistance. Single site Langmuir physisorption and Maxwell Stefan mass transport in micropore were applied. All the data were then optimized to get the best value of modified fitted parameter. The model was in a good agreement with the experiment data. Diffusivity tended to increase by increasing temperatures.Keywords: adsorption, Langmuir, Maxwell-Stefan, natural zeolite, surface diffusion
Procedia PDF Downloads 34911633 GIS Model for Sanitary Landfill Site Selection Based on Geotechnical Parameters
Authors: Hecson Christian, Joel Macwan
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Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.Keywords: GIS, AHP, MCDA, Geo-technical
Procedia PDF Downloads 14411632 An Industrial Scada System Remote Control Using Mobile Phones
Authors: Ahmidah Elgali
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SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.Keywords: control, industrial, mobile, network, remote, SCADA
Procedia PDF Downloads 6911631 Performance Comparison of Deep Convolutional Neural Networks for Binary Classification of Fine-Grained Leaf Images
Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu
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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning
Procedia PDF Downloads 17911630 Optimization of Hybrid off Grid Energy Station
Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih
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Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.Keywords: energy modeling, HOMER, off-grid system, optimization
Procedia PDF Downloads 56011629 Finite Element Analysis of Resonance Frequency Shift of Laminated Composite Beam
Authors: Cheng Yang Kwa, Yoke Rung Wong
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Laminated composite materials are widely employed in automotive, aerospace, and other industries. These materials provide distinct benefits due to their high specific strength, high specific modulus, and ability to be customized for a specific function. However, delamination of laminated composite materials is one of the main defects which can occur during manufacturing, regular operations, or maintenance. Delamination can bring about considerable internal damage, unobservable by visual check, that causes significant loss in strength and stability, leading to composite structure catastrophic failure. Structural health monitoring (SHM) is known to be the automated method for monitoring and evaluating the condition of a monitored object. There are several ways to conduct SHM in aerospace. One of the effective methods is to monitor the natural frequency shift of structure due to the presence of defect. This study investigated the mechanical resonance frequency shift of a multi-layer composite cantilever beam due to interlaminar delamination. ANSYS Workbench® was used to create a 4-plies laminated composite cantilever finite element model with [90/0]s fiber setting. Epoxy Carbon UD (230GPA) Prepreg was chosen, and the thickness was 2.5mm for each ply. The natural frequencies of the finite element model with various degree of delamination were simulated based on modal analysis and then validated by using literature. It was shown that the model without delamination had natural frequency of 40.412 Hz, which was 1.55% different from the calculated result (41.050 Hz). Thereafter, the various degree of delamination was mimicked by changing the frictional conditions at the middle ply-to-ply interface. The results suggested that delamination in the laminated composite cantilever induced a change in its stiffness which alters its mechanical resonance frequency.Keywords: structural health monitoring, NDT, cantilever, laminate
Procedia PDF Downloads 9711628 The Effect of Green Power Trading Mechanism on Interregional Power Generation and Transmission in China
Authors: Yan-Shen Yang, Bai-Chen Xie
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Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model
Procedia PDF Downloads 13311627 Identifying Key Factors for Accidents’ Severity at Rail-Road Level Crossings Using Ordered Probit Models
Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri
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The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors
Procedia PDF Downloads 14211626 Lateral Torsional Buckling Resistance of Trapezoidally Corrugated Web Girders
Authors: Annamária Käferné Rácz, Bence Jáger, Balázs Kövesdi, László Dunai
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Due to the numerous advantages of steel corrugated web girders, its application field is growing for bridges as well as for buildings. The global stability behavior of such girders is significantly larger than those of conventional I-girders with flat web, thus the application of the structural steel material can be significantly reduced. Design codes and specifications do not provide clear and complete rules or recommendations for the determination of the lateral torsional buckling (LTB) resistance of corrugated web girders. Therefore, the authors made a thorough investigation regarding the LTB resistance of the corrugated web girders. Finite element (FE) simulations have been performed to develop new design formulas for the determination of the LTB resistance of trapezoidally corrugated web girders. FE model is developed considering geometrical and material nonlinear analysis using equivalent geometric imperfections (GMNI analysis). The equivalent geometric imperfections involve the initial geometric imperfections and residual stresses coming from rolling, welding and flame cutting. Imperfection sensitivity analysis was performed to determine the necessary magnitudes regarding only the first eigenmodes shape imperfections. By the help of the validated FE model, an extended parametric study is carried out to investigate the LTB resistance for different trapezoidal corrugation profiles. First, the critical moment of a specific girder was calculated by FE model. The critical moments from the FE calculations are compared to the previous analytical calculation proposals. Then, nonlinear analysis was carried out to determine the ultimate resistance. Due to the numerical investigations, new proposals are developed for the determination of the LTB resistance of trapezoidally corrugated web girders through a modification factor on the design method related to the conventional flat web girders.Keywords: corrugated web, lateral torsional buckling, critical moment, FE modeling
Procedia PDF Downloads 27811625 3D Point Cloud Model Color Adjustment by Combining Terrestrial Laser Scanner and Close Range Photogrammetry Datasets
Authors: M. Pepe, S. Ackermann, L. Fregonese, C. Achille
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3D models obtained with advanced survey techniques such as close-range photogrammetry and laser scanner are nowadays particularly appreciated in Cultural Heritage and Archaeology fields. In order to produce high quality models representing archaeological evidences and anthropological artifacts, the appearance of the model (i.e. color) beyond the geometric accuracy, is not a negligible aspect. The integration of the close-range photogrammetry survey techniques with the laser scanner is still a topic of study and research. By combining point cloud data sets of the same object generated with both technologies, or with the same technology but registered in different moment and/or natural light condition, could construct a final point cloud with accentuated color dissimilarities. In this paper, a methodology to uniform the different data sets, to improve the chromatic quality and to highlight further details by balancing the point color will be presented.Keywords: color models, cultural heritage, laser scanner, photogrammetry
Procedia PDF Downloads 27311624 Steady-State Behavior of a Multi-Phase M/M/1 Queue in Random Evolution Subject to Catastrophe Failure
Authors: Reni M. Sagayaraj, Anand Gnana S. Selvam, Reynald R. Susainathan
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In this paper, we consider stochastic queueing models for Steady-state behavior of a multi-phase M/M/1 queue in random evolution subject to catastrophe failure. The arrival flow of customers is described by a marked Markovian arrival process. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. This model contains a repair state, when a catastrophe occurs the system is transferred to the failure state. The paper focuses on the steady-state equation, and observes that, the steady-state behavior of the underlying queueing model along with the average queue size is analyzed.Keywords: M/G/1 queuing system, multi-phase, random evolution, steady-state equation, catastrophe failure
Procedia PDF Downloads 32111623 Nonlinear Modelling of Sloshing Waves and Solitary Waves in Shallow Basins
Authors: Mohammad R. Jalali, Mohammad M. Jalali
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The earliest theories of sloshing waves and solitary waves based on potential theory idealisations and irrotational flow have been extended to be applicable to more realistic domains. To this end, the computational fluid dynamics (CFD) methods are widely used. Three-dimensional CFD methods such as Navier-Stokes solvers with volume of fluid treatment of the free surface and Navier-Stokes solvers with mappings of the free surface inherently impose high computational expense; therefore, considerable effort has gone into developing depth-averaged approaches. Examples of such approaches include Green–Naghdi (GN) equations. In Cartesian system, GN velocity profile depends on horizontal directions, x-direction and y-direction. The effect of vertical direction (z-direction) is also taken into consideration by applying weighting function in approximation. GN theory considers the effect of vertical acceleration and the consequent non-hydrostatic pressure. Moreover, in GN theory, the flow is rotational. The present study illustrates the application of GN equations to propagation of sloshing waves and solitary waves. For this purpose, GN equations solver is verified for the benchmark tests of Gaussian hump sloshing and solitary wave propagation in shallow basins. Analysis of the free surface sloshing of even harmonic components of an initial Gaussian hump demonstrates that the GN model gives predictions in satisfactory agreement with the linear analytical solutions. Discrepancies between the GN predictions and the linear analytical solutions arise from the effect of wave nonlinearities arising from the wave amplitude itself and wave-wave interactions. Numerically predicted solitary wave propagation indicates that the GN model produces simulations in good agreement with the analytical solution of the linearised wave theory. Comparison between the GN model numerical prediction and the result from perturbation analysis confirms that nonlinear interaction between solitary wave and a solid wall is satisfactorilly modelled. Moreover, solitary wave propagation at an angle to the x-axis and the interaction of solitary waves with each other are conducted to validate the developed model.Keywords: Green–Naghdi equations, nonlinearity, numerical prediction, sloshing waves, solitary waves
Procedia PDF Downloads 27811622 A Lagrangian Hamiltonian Computational Method for Hyper-Elastic Structural Dynamics
Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer
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Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.Keywords: Hamilton's principle of least action, particle-based method, hyper-elasticity, analysis of stability
Procedia PDF Downloads 33811621 Experimental and Numerical Study on Energy Absorption Characteristic of a Coupler Rubber Buffer Used in Rail Vehicles
Authors: Zhixiang Li, Shuguang Yao, Wen Ma
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Coupler rubber buffer has been widely applied on the high-speed trains and the main function of the rubber buffer is dissipating the impact energy between vehicles. The rubber buffer consists of two groups of rubbers, which are both pre-compressed and then installed into the frame body. This work focuses on the energy absorption capacity of each group of buffers particularly. The quasi-static compression tests were carried out to obtain the pre-compression force and the load-defection response of the buffers. Then a finite element (FE) model was constructed using Ls_dyna program. The rubber material was modeled with a tabulated method easily, in which no more material constants need to be fitted. The simulation results agreed with the experimental results well. Numerical study of the buffers was performed using the validated FE model and the influence of the initial pressure on the buffers was obtained. In addition, the interaction between the two groups of buffers was also investigated and the optimum distribution of the two was found.Keywords: initial pressure, rubber buffer, simulation, tabulated method
Procedia PDF Downloads 14011620 ADP Approach to Evaluate the Blood Supply Network of Ontario
Authors: Usama Abdulwahab, Mohammed Wahab
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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem
Procedia PDF Downloads 50211619 Modelling and Technical Assessment of Multi-Motor for Electric Vehicle Drivetrains by Using Electric Differential
Authors: Mohamed Abdel-Monem, Gamal Sowilam, Omar Hegazy
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This paper presents a technical assessment of an electric vehicle with two independent rear-wheel motor and an improved traction control system. The electric differential and the control strategy have been implemented to assure that in a straight trajectory, the two rear-wheels run exactly at the same speed, considering the same/different road conditions under the left and right side of the wheels. In case of turning to right/left, the difference between the two rear-wheels speeds assures a vehicle trajectory without sliding, thanks to a harmony between the electric differential and the control strategy. The present article demonstrates a complete model and analysis of a traction control system, considering four different traction scenarios, for two independent rear-wheels motors for electric vehicles. Furthermore, the vehicle model, including wheel dynamics, load forces, electric differential, and control strategy, is designed and verified by using MATLAB/Simulink environment.Keywords: electric vehicle, energy saving, multi-motor, electric differential, simulation and control
Procedia PDF Downloads 34811618 The Magnetized Quantum Breathing in Cylindrical Dusty Plasma
Authors: A. Abdikian
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A quantum breathing mode has been theatrically studied in quantum dusty plasma. By using linear quantum hydrodynamic model, not only the quantum dispersion relation of rotation mode but also void structure has been derived in the presence of an external magnetic field. Although the phase velocity of the magnetized quantum breathing mode is greater than that of unmagnetized quantum breathing mode, attenuation of the magnetized quantum breathing mode along radial distance seems to be slower than that of unmagnetized quantum breathing mode. Clearly, drawing the quantum breathing mode in the presence and absence of a magnetic field, we found that the magnetic field alters the distribution of dust particles and changes the radial and azimuthal velocities around the axis. Because the magnetic field rotates the dust particles and collects them, it could compensate the void structure.Keywords: the linear quantum hydrodynamic model, the magnetized quantum breathing mode, the quantum dispersion relation of rotation mode, void structure
Procedia PDF Downloads 28811617 Multi-Classification Deep Learning Model for Diagnosing Different Chest Diseases
Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury
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Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification
Procedia PDF Downloads 8311616 Validity and Reliability of Competency Assessment Implementation (CAI) Instrument Using Rasch Model
Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman
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This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), in fit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained shows that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.Keywords: competency assessment, reliability, validity, item analysis
Procedia PDF Downloads 44011615 Sequence Analysis and Molecular Cloning of PROTEOLYSIS 6 in Tomato
Authors: Nurulhikma Md Isa, Intan Elya Suka, Nur Farhana Roslan, Chew Bee Lynn
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The evolutionarily conserved N-end rule pathway marks proteins for degradation by the Ubiquitin Proteosome System (UPS) based on the nature of their N-terminal residue. Proteins with a destabilizing N-terminal residue undergo a series of condition-dependent N-terminal modifications, resulting in their ubiquitination and degradation. Intensive research has been carried out in Arabidopsis previously. The group VII Ethylene Response Factor (ERFs) transcription factors are the first N-end rule pathway substrates found in Arabidopsis and their role in regulating oxygen sensing. ERFs also function as central hubs for the perception of gaseous signals in plants and control different plant developmental including germination, stomatal aperture, hypocotyl elongation and stress responses. However, nothing is known about the role of this pathway during fruit development and ripening aspect. The plant model system Arabidopsis cannot represent fleshy fruit model system therefore tomato is the best model plant to study. PROTEOLYSIS6 (PRT6) is an E3 ubiquitin ligase of the N-end rule pathway. Two homologs of PRT6 sequences have been identified in tomato genome database using the PRT6 protein sequence from model plant Arabidopsis thaliana. Homology search against Ensemble Plant database (tomato) showed Solyc09g010830.2 is the best hit with highest score of 1143, e-value of 0.0 and 61.3% identity compare to the second hit Solyc10g084760.1. Further homology search was done using NCBI Blast database to validate the data. The result showed best gene hit was XP_010325853.1 of uncharacterized protein LOC101255129 (Solanum lycopersicum) with highest score of 1601, e-value 0.0 and 48% identity. Both Solyc09g010830.2 and uncharacterized protein LOC101255129 were genes located at chromosome 9. Further validation was carried out using BLASTP program between these two sequences (Solyc09g010830.2 and uncharacterized protein LOC101255129) to investigate whether they were the same proteins represent PRT6 in tomato. Results showed that both proteins have 100 % identity, indicates that they were the same gene represents PRT6 in tomato. In addition, we used two different RNAi constructs that were driven under 35S and Polygalacturonase (PG) promoters to study the function of PRT6 during tomato developmental stages and ripening processes.Keywords: ERFs, PRT6, tomato, ubiquitin
Procedia PDF Downloads 23611614 The Effect of Group Counseling on the Victimhood Perceptions of Adolescent Who Are the Subject of Peer Victimization and on Their Coping Strategies
Authors: İsmail Seçer, Taştan Seçer
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In this study, the effect of the group counseling on the victimhood perceptions of the primary school 7th and 8th grade students who are determined to be the subject of peer victimization and their dealing way with it was analyzed. The research model is Solomon Four Group Experimental Model. In this model, there are four groups that were determined with random sampling. Two of the groups have been used as experimental group and the other two have been used as control group. Solomon model is defined as real experimental model. In real experimental models, there are multiple groups consisting of subject which have similar characteristics, and selection of the subjects is done with random sampling. For this purpose, 230 students from Kültür Kurumu Primary School in Erzurum were asked to fill Adolescent Peer Victim Form. 100 students whose victim scores were higher and who were determined to be the subject of bullying were talked face to face and informed about the current study, and they were asked if they were willing to participate or not. As a result of these interviews, 60 students were determined to participate in the experimental study and four group consisting of 15 people were created with simple random sampling method. After the groups had been formed, experimental and control group were determined with casting lots. After determining experimental and control groups, an 11-session group counseling activity which was prepared by the researcher according to the literature was applied. The purpose of applying group counseling is to change the ineffective dealing ways with bullying and their victimhood perceptions. Each session was planned to be 75 minutes and applied as planned. In the control groups, counseling activities in the primary school counseling curricula was applied for 11 weeks. As a result of the study, physical, emotional and verbal victimhood perceptions of the participants in the experimental groups were decreased significantly compared to pre-experimental situations and to those in control group. Besides, it was determined that this change observed in the victimhood perceptions of the experimental group occurred independently from the effect of variables such as gender, age and academic success. The first evidence of the study related to the dealing ways is that the scores of the participants in the experimental group related to the ineffective dealing ways such as despair and avoidance is decreased significantly compared to the pre-experimental situation and to those in control group. The second evidence related to the dealing ways is that the scores of the participants in the experimental group related to effective dealing ways such as seeking for help, consulting social support, resistance and optimism is increased significantly compared to the pre-experimental situation and to those in control group. According to the evidence obtained through the study, it can be said that group counseling is an effective approach to change the victimhood perceptions of the individuals who are the subject of bullying and their dealing strategies with it.Keywords: bullying, perception of victimization, coping strategies, ancova analysis
Procedia PDF Downloads 38511613 Establishment of the Regression Uncertainty of the Critical Heat Flux Power Correlation for an Advanced Fuel Bundle
Authors: L. Q. Yuan, J. Yang, A. Siddiqui
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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method
Procedia PDF Downloads 40811612 Lead Removal From Ex- Mining Pond Water by Electrocoagulation: Kinetics, Isotherm, and Dynamic Studies
Authors: Kalu Uka Orji, Nasiman Sapari, Khamaruzaman W. Yusof
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Exposure of galena (PbS), tealite (PbSnS2), and other associated minerals during mining activities release lead (Pb) and other heavy metals into the mining water through oxidation and dissolution. Heavy metal pollution has become an environmental challenge. Lead, for instance, can cause toxic effects to human health, including brain damage. Ex-mining pond water was reported to contain lead as high as 69.46 mg/L. Conventional treatment does not easily remove lead from water. A promising and emerging treatment technology for lead removal is the application of the electrocoagulation (EC) process. However, some of the problems associated with EC are systematic reactor design, selection of maximum EC operating parameters, scale-up, among others. This study investigated an EC process for the removal of lead from synthetic ex-mining pond water using a batch reactor and Fe electrodes. The effects of various operating parameters on lead removal efficiency were examined. The results obtained indicated that the maximum removal efficiency of 98.6% was achieved at an initial PH of 9, the current density of 15mA/cm2, electrode spacing of 0.3cm, treatment time of 60 minutes, Liquid Motion of Magnetic Stirring (LM-MS), and electrode arrangement = BP-S. The above experimental data were further modeled and optimized using a 2-Level 4-Factor Full Factorial design, a Response Surface Methodology (RSM). The four factors optimized were the current density, electrode spacing, electrode arrangements, and Liquid Motion Driving Mode (LM). Based on the regression model and the analysis of variance (ANOVA) at 0.01%, the results showed that an increase in current density and LM-MS increased the removal efficiency while the reverse was the case for electrode spacing. The model predicted the optimal lead removal efficiency of 99.962% with an electrode spacing of 0.38 cm alongside others. Applying the predicted parameters, the lead removal efficiency of 100% was actualized. The electrode and energy consumptions were 0.192kg/m3 and 2.56 kWh/m3 respectively. Meanwhile, the adsorption kinetic studies indicated that the overall lead adsorption system belongs to the pseudo-second-order kinetic model. The adsorption dynamics were also random, spontaneous, and endothermic. The higher temperature of the process enhances adsorption capacity. Furthermore, the adsorption isotherm fitted the Freundlish model more than the Langmuir model; describing the adsorption on a heterogeneous surface and showed good adsorption efficiency by the Fe electrodes. Adsorption of Pb2+ onto the Fe electrodes was a complex reaction, involving more than one mechanism. The overall results proved that EC is an efficient technique for lead removal from synthetic mining pond water. The findings of this study would have application in the scale-up of EC reactor and in the design of water treatment plants for feed-water sources that contain lead using the electrocoagulation method.Keywords: ex-mining water, electrocoagulation, lead, adsorption kinetics
Procedia PDF Downloads 14311611 Preparation on Sentimental Analysis on Social Media Comments with Bidirectional Long Short-Term Memory Gated Recurrent Unit and Model Glove in Portuguese
Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura
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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU
Procedia PDF Downloads 15011610 SVID: Structured Vulnerability Intelligence for Building Deliberated Vulnerable Environment
Authors: Wenqing Fan, Yixuan Cheng, Wei Huang
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The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence
Procedia PDF Downloads 11411609 A Comparison of Computational and Experimental Data to Investigate the Influence of the Tangential Velocity of Inner Rotating Wall on Axial Velocity Profile of Flow through Vertical Annular Pipe with Rotating Inner Surface
Authors: Abdusalam Sharf
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In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall
Procedia PDF Downloads 37211608 Impact Analysis of Transportation Modal Shift on Regional Energy Consumption and Environmental Level: Focused on Electric Automobiles
Authors: Hong Bae Kim, Chang Ho Hur
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Many governments have tried to reduce CO2 emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO2 emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO2 emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.Keywords: electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model
Procedia PDF Downloads 29511607 Development of Natural Zeolites Adsorbent: Preliminary Study on Water-Isopropyl Alcohol Adsorption in a Close-Loop Continuous Adsorber
Authors: Sang Kompiang Wirawan, Pandu Prabowo Jati, I Wayan Warmada
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Klaten Indonesian natural zeolite can be used as powder or pellet adsorbent. Pellet adsorbent has been made from activated natural zeolite powder by a conventional pressing method. Starch and formaldehyde were added as binder to strengthen the construction of zeolite pellet. To increase the absorptivity and its capacity, natural zeolite was activated first chemically and thermally. This research examined adsorption process of water from Isopropyl Alcohol (IPA)-water system using zeolite adsorbent pellet from natural zeolite powder which has been activated with H2SO4 0.1 M and 0.3 M. Adsorbent was pelleted by pressing apparatus at certain pressure to make specification in 1.96 cm diameter, 0.68 cm thickness which the natural zeolite powder (-80 mesh). The system of isopropyl-alcohol water contained 80% isopropyl-alcohol. Adsorption process was held in close-loop continuous apparatus which the zeolite pellet was put inside a column and the solution of IPA-water was circulated at certain flow. Concentration changing was examined thoroughly at a certain time. This adsorption process included mass transfer from bulk liquid into film layer and from film layer into the solid particle. Analysis of rate constant was using first order isotherm model that simulated with MATLAB. Besides using first order isotherm, intra-particle diffusion model was proposed by using pore diffusion model. The study shows that adsorbent activated by H2SO4 0.1 M has good absorptivity with mass transfer constant at 0.1286 min-1.Keywords: intra-particle diffusion, fractional attainment, first order isotherm, zeolite
Procedia PDF Downloads 30411606 YOLO-IR: Infrared Small Object Detection in High Noise Images
Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long
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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion
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