Search results for: electrical machine design
6230 Land Suitability Prediction Modelling for Agricultural Crops Using Machine Learning Approach: A Case Study of Khuzestan Province, Iran
Authors: Saba Gachpaz, Hamid Reza Heidari
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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. This necessitates increased resource consumption and underscores the importance of addressing sustainable agriculture development along with other environmental considerations. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for 10 different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.
Keywords: Land suitability, machine learning, random forest, sustainable agriculture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2826229 Parametric Optimization of Hospital Design
Authors: M. K. Holst, P. H. Kirkegaard, L. D. Christoffersen
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Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences.Keywords: Architectural Layout Design, Hospital Design, Parametric design, Performance-based models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27176228 Application of Artificial Neural Network in the Investigation of Bearing Defects
Authors: S. Sendhil Kumar, M. Senthil Kumar
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Maintenance and design engineers have great concern for the functioning of rotating machineries due to the vibration phenomenon. Improper functioning in rotating machinery originates from the damage to rolling element bearings. The status of rolling element bearings require advanced technologies to monitor their health status efficiently and effectively. Avoiding vibration during machine running conditions is a complicated process. Vibration simulation should be carried out using suitable sensors/ transducers to recognize the level of damage on bearing during machine operating conditions. Various issues arising in rotating systems are interlinked with bearing faults. This paper presents an approach for fault diagnosis of bearings using neural networks and time/frequencydomain vibration analysis.Keywords: Bearing vibration, Condition monitoring, Fault diagnosis, Frequency domain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25186227 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents
Authors: Chothmal, Basant Agarwal
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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33036226 Benefits from a SMED Application in a Punching Machine
Authors: Eric Costa, Sara Bragança, Rui Sousa, Anabela Alves
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This paper presents an application of the Single-Minute Exchange of Die (SMED) methodology to a turret punching machine in an elevators company, in Portugal. The work was developed during five months, in the ambit of a master thesis in Industrial Engineering and Management. The Lean Production tool SMED was applied to reduce setup times in order to improve the production flexibility of the machine. The main results obtained were a reduction of 64% in setup time (from 15.1 to 5.4min), 50% in work-in-process amount (from 12.8 to 6.4 days) and 99% in the distance traveled by the operator during the internal period (from 136.7 to 1.7m). These improvements correspond to gains of about €7,315.38 per year.
Keywords: Lean production, setup process, SMED.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40826225 Design and Implementation of a Software Platform Based on Artificial Intelligence for Product Recommendation
Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano
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Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.
Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3236224 Solving the Nonlinear Heat Conduction in a Spherical Coordinate with Electrical Simulation
Authors: A. M. Gheitaghy, H. Saffari, G. Q. Zhang
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Numerical approach based on the electrical simulation method is proposed to solve a nonlinear transient heat conduction problem with nonlinear boundary for a spherical body. This problem represents a strong nonlinearity in both the governing equation for temperature dependent thermal property and the boundary condition for combined convective and radiative cooling. By analysing the equivalent electrical model using the electrical circuit simulation program HSPICE, transient temperature and heat flux distributions at sphere can be obtained easily and fast. The solutions clearly illustrate the effect of the radiation-conduction parameter Nrc, the Biot number and the linear coefficient of temperature dependent conductivity and heat capacity. On comparing the results with corresponding numerical solutions, the accuracy and efficiency of this computational method is found to be good.Keywords: Convective boundary, radiative boundary, electrical simulation method, nonlinear heat conduction, spherical coordinate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13896223 Pose-Dependency of Machine Tool Structures: Appearance, Consequences, and Challenges for Lightweight Large-Scale Machines
Authors: S. Apprich, F. Wulle, A. Lechler, A. Pott, A. Verl
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Large-scale machine tools for the manufacturing of large work pieces, e.g. blades, casings or gears for wind turbines, feature pose-dependent dynamic behavior. Small structural damping coefficients lead to long decay times for structural vibrations that have negative impacts on the production process. Typically, these vibrations are handled by increasing the stiffness of the structure by adding mass. This is counterproductive to the needs of sustainable manufacturing as it leads to higher resource consumption both in material and in energy. Recent research activities have led to higher resource efficiency by radical mass reduction that is based on controlintegrated active vibration avoidance and damping methods. These control methods depend on information describing the dynamic behavior of the controlled machine tools in order to tune the avoidance or reduction method parameters according to the current state of the machine. This paper presents the appearance, consequences and challenges of the pose-dependent dynamic behavior of lightweight large-scale machine tool structures in production. It starts with the theoretical introduction of the challenges of lightweight machine tool structures resulting from reduced stiffness. The statement of the pose-dependent dynamic behavior is corroborated by the results of the experimental modal analysis of a lightweight test structure. Afterwards, the consequences of the pose-dependent dynamic behavior of lightweight machine tool structures for the use of active control and vibration reduction methods are explained. Based on the state of the art of pose-dependent dynamic machine tool models and the modal investigation of an FE-model of the lightweight test structure, the criteria for a pose-dependent model for use in vibration reduction are derived. The description of the approach for a general posedependent model of the dynamic behavior of large lightweight machine tools that provides the necessary input to the aforementioned vibration avoidance and reduction methods to properly tackle machine vibrations is the outlook of the paper.Keywords: Dynamic behavior, lightweight, machine tool, pose-dependency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28436222 A Dual Fitness Function Genetic Algorithm: Application on Deterministic Identical Machine Scheduling
Authors: Saleem Z. Ramadan, Gürsel A. Süer
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In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.
Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20686221 Oil Palm Empty Fruit Bunch as a New Organic Filler for Electrical Tree Inhibition
Authors: M. H. Ahmad, A. A. A. Jamil, H. Ahmad, M. A. M. Piah, A. Darus, Y. Z. Arief, N. Bashir
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The use of synthetic retardants in polymeric insulated cables is not uncommon in the high voltage engineering to study electrical treeing phenomenon. However few studies on organic materials for the same investigation have been carried. .This paper describes the study on the effects of Oil Palm Empty Fruit Bunch (OPEFB) microfiller on the tree initiation and propagation in silicone rubber with different weight percentages (wt %) of filler to insulation bulk material. The weight percentages used were 0 wt % and 1 wt % respectively. It was found that the OPEFB retards the propagation of the electrical treeing development. For tree inception study, the addition of 1(wt %) OPEFB has increase the tree inception voltage of silicone rubber. So, OPEFB is a potential retardant to the initiation and growth of electrical treeing occurring in polymeric materials for high voltage application. However more studies on the effects of physical and electrical properties of OPEFB as a tree retardant material are required.Keywords: Oil palm empty fruit bunch, electrical tree, siliconerubber, fillers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23616220 Highly Conductive Polycrystalline Metallic Ring in a Magnetic Field
Authors: Isao Tomita
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Electrical conduction in a quasi-one-dimensional polycrystalline metallic ring with a long electron phase coherence length realized at low temperature is investigated. In this situation, the wave nature of electrons is important in the ring, where the electrical current I can be induced by a vector potential that arises from a static magnetic field applied perpendicularly to the ring’s area. It is shown that if the average grain size of the polycrystalline ring becomes large (or comparable to the Fermi wavelength), the electrical current I increases to ~I0, where I0 is a current in a disorder-free ring. The cause of this increasing effect is examined, and this takes place if the electron localization length in the polycrystalline potential increases with increasing grain size, which gives rise to coherent connection of tails of a localized electron wave function in the ring and thus provides highly coherent electrical conduction.Keywords: Electrical Conduction, Electron Phase Coherence, Polycrystalline Metal, Magnetic Field.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16306219 Sentiment Analysis: Comparative Analysis of Multilingual Sentiment and Opinion Classification Techniques
Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel
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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.
Keywords: Cross-language analysis, machine learning, machine translation, sentiment analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16646218 Silicon Nanowire for Thermoelectric Applications: Effects of Contact Resistance
Authors: Y. Li, K. Buddharaju, N. Singh, G. Q. Lo, S. J. Lee
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Silicon nanowire (SiNW) based thermoelectric device (TED) has potential applications in areas such as chip level cooling/ energy harvesting. It is a great challenge however, to assemble an efficient device with these SiNW. The presence of parasitic in the form of interfacial electrical resistance will have a significant impact on the performance of the TED. In this work, we explore the effect of the electrical contact resistance on the performance of a TED. Numerical simulations are performed on SiNW to investigate such effects on its cooling performance. Intrinsically, SiNW individually without the unwanted parasitic effect has excellent cooling power density. However, the cooling effect is undermined with the contribution of the electrical contact resistance.
Keywords: Thermoelectric, silicon, nanowire, electrical contact resistance, parasitics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21036217 Analysis of an Electrical Transformer: A Bond Graph Approach
Authors: Gilberto Gonzalez-A
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Bond graph models of an electrical transformer including the nonlinear saturation are presented. These models determine the relation between self and mutual inductances, and the leakage and magnetizing inductances of power transformers with two and three windings using the properties of a bond graph. The modelling and analysis using this methodology to three phase power transformers or transformers with internal incipient faults can be extended.Keywords: Bond graph, electrical transformer, nonlinear saturation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15396216 Diagnosis of Induction Machine Faults by DWT
Authors: Hamidreza Akbari
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In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.
Keywords: Induction machine, Fault, DWT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21306215 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models
Authors: [email protected]
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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data need a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM), ensemble learning with hyper parameters optimization, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.
Keywords: Machine learning, Deep learning, cancer prediction, breast cancer, LSTM, Score-Level Fusion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3996214 A Neural Network Approach for an Automatic Detection and Localization of an Open Phase Circuit of a Five-Phase Induction Machine Used in a Drivetrain of an Electric Vehicle
Authors: S. Chahba, R. Sehab, A. Akrad, C. Morel
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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.
Keywords: Electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit fault diagnosis, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4486213 Optimal Analysis of Grounding System Design for Distribution Substation
Authors: T. Lantharthong, N. Rugthaicharoencheep, A. Phayomhom
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This paper presents the electrical effect of two neighboring distribution substation during the construction phase. The size of auxiliary grounding grid have an effect on entire grounding system. The bigger the size of auxiliary grounding grid, the lower the GPR and maximum touch voltage, with the exception that when the two grids are unconnected, i.e. the bigger the size of auxiliary grounding grid, the higher the maximum step voltage. The results in this paper could be served as design guideline of grounding system, and perhaps remedy of some troublesome grounding grids in power distribution’s system. Modeling and simulation is carried out on the Current Distribution Electromagnetic interference Grounding and Soil structure (CDEGS) program. The simulation results exhibit the design and analysis of power system grounding and perhaps could be set as a standard in grounding system design and modification in distribution substations.
Keywords: Grounding System, Touch Voltage, Step Voltage, Safety Criteria.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26806212 Solving Machine Loading Problem in Flexible Manufacturing Systems Using Particle Swarm Optimization
Authors: S. G. Ponnambalam, Low Seng Kiat
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In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve machine loading problem in flexible manufacturing system (FMS), with bicriterion objectives of minimizing system unbalance and maximizing system throughput in the occurrence of technological constraints such as available machining time and tool slots. A mathematical model is used to select machines, assign operations and the required tools. The performance of the PSO is tested by using 10 sample dataset and the results are compared with the heuristics reported in the literature. The results support that the proposed PSO is comparable with the algorithms reported in the literature.Keywords: Machine loading problem, FMS, Particle Swarm Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21196211 Analytical Model Based Evaluation of Human Machine Interfaces Using Cognitive Modeling
Authors: Belkacem Chikhaoui, Helene Pigot
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Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15306210 Remote Operation of CNC Milling Through Virtual Simulation and Remote Desktop Interface
Authors: Afzeri, A.G.E Sujtipto, R. Muhida, M. Konneh, Darmawan
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Increasing the demand for effectively use of the production facility requires the tools for sharing the manufacturing facility through remote operation of the machining process. This research introduces the methodology of machining technology for direct remote operation of networked milling machine. The integrated tools with virtual simulation, remote desktop protocol and Setup Free Attachment for remote operation of milling process are proposed. Accessing and monitoring of machining operation is performed by remote desktop interface and 3D virtual simulations. Capability of remote operation is supported by an auto setup attachment with a reconfigurable pin type setup free technology installed on the table of CNC milling machine to perform unattended machining process. The system is designed using a computer server and connected to a PC based controlled CNC machine for real time monitoring. A client will access the server through internet communication and virtually simulate the machine activity. The result has been presented that combination between real time virtual simulation and remote desktop tool is enabling to operate all machine tool functions and as well as workpiece setup..Keywords: Remote Desktop, PC Based CNC, Remote Machining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28776209 A Study on Roles of the Community Design in Crime Prevention: Focusing on Project called Root out Crime by Design in South Korea
Authors: Miyoun Won, Youngkyung Choi
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In the meantime, there were lots of hardware solutions like products or urban facilities for crime prevention in the public design area. Meanwhile, people have growing interest in public design so by making a village; community design in public design is getting active by the society. The system for crime prevention is actively done by the citizens who created the community. Regarding the social situation, in this project, we saw it as a kind of community design practices and researched about 'how does community design influence Crime prevention?' The purpose of this study is to propose the community design as a way of preventing the crime in the city. First, we found out about the definition, elements and methods of community design by reviewing the theory. And then, this study analyzed the case that was enforced in Seoul and organize the elements and methods of community design. This study can be refer to Public Design based on civil participation and make the community design area contribute to expand the way of solving social problems.
Keywords: Public Design, Sustainable Community Design, Crime Prevention, Participatory Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21476208 A Risk Assessment Tool for the Contamination of Aflatoxins on Dried Figs based on Machine Learning Algorithms
Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios
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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity and aflatoxinogenic capacity of the strains, topography, soil and climate parameters of the fig orchards are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high-performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques i.e., dimensionality reduction on the original dataset (Principal Component Analysis), metric learning (Mahalanobis Metric for Clustering) and K-nearest Neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson Correlation Coefficient (PCC) between observed and predicted values.
Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6476207 New Gate Stack Double Diffusion MOSFET Design to Improve the Electrical Performances for Power Applications
Authors: Z. Dibi, F. Djeffal, N. Lakhdar
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In this paper, we have developed an explicit analytical drain current model comprising surface channel potential and threshold voltage in order to explain the advantages of the proposed Gate Stack Double Diffusion (GSDD) MOSFET design over the conventional MOSFET with the same geometric specifications that allow us to use the benefits of the incorporation of the high-k layer between the oxide layer and gate metal aspect on the immunity of the proposed design against the self-heating effects. In order to show the efficiency of our proposed structure, we propose the simulation of the power chopper circuit. The use of the proposed structure to design a power chopper circuit has showed that the (GSDD) MOSFET can improve the working of the circuit in terms of power dissipation and self-heating effect immunity. The results so obtained are in close proximity with the 2D simulated results thus confirming the validity of the proposed model.Keywords: Double-Diffusion, modeling, MOSFET, power.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15846206 Optimization for the Hydraulic Clamping System of an Internal Circulation Two-Platen Injection Molding Machine
Authors: Jian Wang, Lu Yang, Jiong Peng
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Internal circulation two-platen clamping system for injection molding machine (IMM) has many potential advantages on energy-saving. In order to estimate its properties, experiments were carried out in this paper. Displacement and pressure of the components were measured. In comparison, the model of hydraulic clamping system was established by using AMESim. The related parameters as well as the energy consumption could be calculated. According to the analysis, the hydraulic system was optimized in order to reduce the energy consumption.
Keywords: AMESim, energy-saving, injection molding machine, internal circulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28396205 Design of Smart Energy Monitoring System for Green IT Life
Authors: Min Goo Lee, Yong Kuk Park, Kyung Kwon Jung, Jun Jae Yoo
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This paper describes the smart energy monitoring system with a wireless sensor network for monitoring of electrical usage in smart house. Proposed system is composed of wireless plugs and energy control wallpad server. The wireless plug integrates an AC power socket, a relay to switch the socket ON/OFF, a Hall effect sensor to sense current of load appliance and a Kmote. The Kmote is a wireless communication interface based on TinyOS. We evaluated wireless plug in a laboratory, analyzed and presented energy consumption data from electrical appliances for 3 months in home.
Keywords: smart house, energy monitoring, wireless plug, wireless sensor network, current consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20486204 Electrical Impedance Imaging Using Eddy Current
Authors: A. Ambia, T. Takemae, Y. Kosugi, M. Hongo
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Electric impedance imaging is a method of reconstructing spatial distribution of electrical conductivity inside a subject. In this paper, a new method of electrical impedance imaging using eddy current is proposed. The eddy current distribution in the body depends on the conductivity distribution and the magnetic field pattern. By changing the position of magnetic core, a set of voltage differences is measured with a pair of electrodes. This set of voltage differences is used in image reconstruction of conductivity distribution. The least square error minimization method is used as a reconstruction algorithm. The back projection algorithm is used to get two dimensional images. Based on this principle, a measurement system is developed and some model experiments were performed with a saline filled phantom. The shape of each model in the reconstructed image is similar to the corresponding model, respectively. From the results of these experiments, it is confirmed that the proposed method is applicable in the realization of electrical imaging.Keywords: Back projection algorithm, electrical impedancetomography, eddy current, magnetic inductance tomography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16956203 An Empirical Dynamic Fuel Cell Model Used for Power System Verification in Aerospace
Authors: Giuliano Raimondo, Jörg Wangemann, Peer Drechsel
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In systems development involving Fuel Cells generators, it is important to have from an early stage of the project a dynamic model for the electrical behavior of the stack to be shared between involved development parties. It allows independent and early design and tests of fuel cell related power electronic. This paper presents an empirical Fuel Cell system model derived from characterization tests on a real system. Moreover, it is illustrated how the obtained model is used to build and validate a real-time Fuel Cell system emulator which is used for aerospace electrical integration testing activities.
Keywords: Fuel cell dynamics, real time simulation, fuel cell, modelling, testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10796202 Wavelet Transform and Support Vector Machine Approach for Fault Location in Power Transmission Line
Authors: V. Malathi, N.S.Marimuthu
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This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in estimating fault location. The results demonstrated the ability of SVM to generalize the situation from the provided patterns and to accurately estimate the location of faults with varying fault resistance.Keywords: Fault location, support vector machine, supportvector regression, transmission lines, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21836201 Extracting Multiword Expressions in Machine Translation from English to Urdu using Relational Data Approach
Authors: Kashif Bilal, Uzair Muhammad, Atif Khan, M. Nasir Khan
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Machine Translation, (hereafter in this document referred to as the "MT") faces a lot of complex problems from its origination. Extracting multiword expressions is also one of the complex problems in MT. Finding multiword expressions during translating a sentence from English into Urdu, through existing solutions, takes a lot of time and occupies system resources. We have designed a simple relational data approach, in which we simply set a bit in dictionary (database) for multiword, to find and handle multiword expression. This approach handles multiword efficiently.Keywords: Machine Translation, Multiword Expressions, Urdulanguage processing, POS (stands for Parts of Speech) Tagging forUrdu, Expert Systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2357