Search results for: dynamic panel data models

Authors: Maziar Ramezani, Zaidi Mohd Ripin

Abstract:

In a metal forming process, the friction between the material and the tools influences the process by modifying the stress distribution of the workpiece. This frictional behaviour is often taken into account by using a constant coefficient of friction in the finite element simulations of sheet metal forming processes. However, friction coefficient varies in time and space with many parameters. The Stribeck friction model is investigated in this study to predict springback behaviour of AA6061-T4 sheets during V-bending process. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The plane-strain bending process is simulated in ABAQUS/Standard. We compared the computed punch load-stroke curves and springback related to the constant coefficient of friction with the defined friction model. The results clearly showed that the new friction model provides better agreement between experiments and results of numerical simulations. The influence of friction models on stress distribution in the workpiece is also studied numerically

Keywords: Friction model, Stress distribution, V-bending.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2697

Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

Abstract:

Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 815

Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

Abstract:

Erosion in a pipe bends caused by particles is a major concern in the oil and gas fields and might cause breakdown to production equipment. This work investigates the effect of sand particle transport in an elbow using computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model is employed to calculate the air/solid particle flow in the elbow. Generic erosion model in Ansys fluent and three particle rebound models are used to predict the erosion rate on the 90° elbows. The model result is compared with experimental data from the open literature validating the CFD-based predictions which reveals that due to the sand particles impinging on the wall of the elbow at high velocity, a point on the pipe elbow were observed to have started turning red due to velocity increase and the maximum erosion locations occur at 48°.

Keywords: Erosion, prediction, elbow, computational fluid dynamics, CFD.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 406

Authors: Carolin Lutz, Jörg Matthes, Patrick Waibel, Ulrich Precht, Krassimir Garbev, Günter Beuchle, Uwe Schweike, Peter Stemmermann, Hubert B. Keller

Abstract:

Online measurement of the product quality is a challenging task in cement production, especially in the production of Celitement, a novel environmentally friendly hydraulic binder. The mineralogy and chemical composition of clinker in ordinary Portland cement production is measured by X-ray diffraction (XRD) and X-ray fluorescence (XRF), where only crystalline constituents can be detected. But only a small part of the Celitement components can be measured via XRD, because most constituents have an amorphous structure. This paper describes the development of algorithms suitable for an on-line monitoring of the final processing step of Celitement based on NIR-data. For calibration intermediate products were dried at different temperatures and ground for variable durations. The products were analyzed using XRD and thermogravimetric analyses together with NIR-spectroscopy to investigate the dependency between the drying and the milling processes on one and the NIR-signal on the other side. As a result, different characteristic parameters have been defined. A short overview of the Celitement process and the challenging tasks of the online measurement and evaluation of the product quality will be presented. Subsequently, methods for systematic development of near-infrared calibration models and the determination of the final calibration model will be introduced. The application of the model on experimental data illustrates that NIR-spectroscopy allows for a quick and sufficiently exact determination of crucial process parameters.

Keywords: Calibration model, celitement, cementitious material, NIR spectroscopy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1674

Authors: L. A. S. Dionel, B. A. P. Santos, V. C. P. Lopes, L. G. Vasconcelos, M. A. Soares, E. B. Morais

Abstract:

This study investigated the biosorption of the azo dye reactive Black B (RBB) from aqueous solution using the nonviable biomass of Cladosporium cladosporioides LM1. The biosorption systems were carried out in batch mode considering different conditions of initial pH, contact time, temperature, initial dye concentration and biosorbent dosage. Higher removal rate of RBB was obtained at pH 2. Biosorption data were successfully described by pseudo-second-order kinetic model and Langmuir isotherm model with the maximum monolayer biosorption capacity estimated at 71.43 mg/g. The values of thermodynamic parameters such as ∆G°, ∆H° and ∆S° indicated that the biosorption of RBB onto fungal biomass was spontaneous and exothermic in nature. It can be concluded that nonviable biomass of Cladosporium cladosporioides LM1 may be an attractive low-cost biosorbent for the removal of azo dye RBB from aqueous solution.

Keywords: Color removal, isotherms and kinetics models, thermodynamic studies, fungus.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 790

Authors: Asif Mansoor, Nasiruddin Khan, Noreen Jamil

Abstract:

In this communication a quantitative modeling approach is applied to construct model for the exchange of gases from open sewer channel to the atmosphere. The data for the exchange of gases of the open sewer channel for the year January 1979 to December 2006 is utilized for the construction of the model. The study reveals that stream flow of the open sewer channel exchanges the toxic gases continuously with time varying scale. We find that the quantitative modeling approach is more parsimonious model for these exchanges. The usual diagnostic tests are applied for the model adequacy. This model is beneficial for planner and managerial bodies for the improvement of implemented policies to overcome future environmental problems.

Keywords: Open sewer channel, Industrial waste, Municipalwaste, Gases exchange, Atmosphere, Stochastic models, Diagnosticschecks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1512

Authors: A. Mourtzikou, D. Sygkridou, T. Georgakopoulos, G. Katsagounos, E. Stathatos

Abstract:

Over 60% highly transparent quasi-solid-state dye-sensitized solar cells (DSSCs) with dimension of 50x50 cm² were fabricated via inkjet printing process using nanocomposite inks as raw materials and tested under outdoor illumination conditions. The cells were electrically characterized, and their possible application to the shell of greenhouses was also examined. The panel design was in Z-interconnection, where the working electrode was inkjet printed on one conductive glass and the counter electrode on a second glass in a sandwich configuration. Silver current collective fingers were printed on the glasses to make the internal electrical connections. In that case, the adjacent cells were connected in series via silver fingers and finally insulated using a UV curing resin to protect them from the corrosive (I^-/I₃^-) redox couple of the electrolyte.

Keywords: Dye-sensitized solar panels, inkjet printing, quasi-solid-state electrolyte, semi-transparency, scale up.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 718

Authors: Zhen-Hui Hu, Jyh-Shong Ju, Ming-Hwei Perng

Abstract:

This paper presents a useful sub-pixel image registration method using line segments and a sub-pixel edge detector. In this approach, straight line segments are first extracted from gray images at the pixel level before applying the sub-pixel edge detector. Next, all sub-pixel line edges are mapped onto the orientation-distance parameter space to solve for line correspondence between images. Finally, the registration parameters with sub-pixel accuracy are analytically solved via two linear least-square problems. The present approach can be applied to various fields where fast registration with sub-pixel accuracy is required. To illustrate, the present approach is applied to the inspection of printed circuits on a flat panel. Numerical example shows that the present approach is effective and accurate when target images contain a sufficient number of line segments, which is true in many industrial problems.

Keywords: Defect detection, Image registration, Straight line segment, Sub-pixel.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1917

Authors: Hyun-Woo Cho

Abstract:

Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1708

Authors: Lihui Ma, Kunlun Xin, Suiqing Liu

Abstract:

Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.

Keywords: Metamodeling, model calibration, radial basisfunction, water distribution system, water quality model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1966

Authors: André Smith, Amr Abdel-Dayem

Abstract:

The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: Colour data, local stereo matching, stereo correspondence, disparity map.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 861

Authors: M. Ezzat, Y. Zaghloul, T. Sorour, A. Hefny, M. Eid

Abstract:

Ultimate capacity of large diameter bored piles is usually determined from pile loading tests as recommended by several international codes and foundation design standards. However, loading of this type of piles till achieving apparent failure is practically seldom. In this paper, numerical analyses are carried out to simulate load test of a large diameter bored pile performed at the location of Alzey highway bridge project (Germany). Test results of pile load settlement relationship till failure as well as results of the base and shaft resistances are available. Apparent failure was indicated in this test by the significant increase of the induced settlement during the last load increment applied on the pile head. Measurements of this pile load test are used to assess the quality of the numerical models investigated. Three different material soil models are implemented in the analyses: Mohr coulomb (MC), Soft soil (SS), and Modified Mohr coulomb (MMC). Very good agreement is obtained between the field measured settlement and the calculated settlement using the MMC model. Results of analysis showed also that the MMC constitutive model is superior to MC, and SS models in predicting the ultimate base and shaft resistances of the large diameter bored pile. After calibrating the numerical model, behavior of large diameter bored piles under axial loads is discussed and the formation of the plastic zone around the pile is explored. Results obtained showed that the plastic zone below the base of the pile at failure extended laterally to about four times the pile diameter and vertically to about three times the pile diameter.

Keywords: Ultimate capacity, large diameter bored piles, plastic zone, failure, pile load test.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 856

Authors: Kashif Kamran, Farooque Azam

Abstract:

The policies governing the business of any organization are well reflected in her business rules. The business rules are implemented by data validation techniques, coded during the software development process. Any change in business policies results in change in the code written for data validation used to enforce the business policies. Implementing the change in business rules without changing the code is the objective of this paper. The proposed approach enables users to create rule sets at run time once the software has been developed. The newly defined rule sets by end users are associated with the data variables for which the validation is required. The proposed approach facilitates the users to define business rules using all the comparison operators and Boolean operators. Multithreading is used to validate the data entered by end user against the business rules applied. The evaluation of the data is performed by a newly created thread using an enhanced form of the RPN (Reverse Polish Notation) algorithm.

Keywords: Business Rules, data validation, multithreading, Reverse Polish Notation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2229

Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

Abstract:

E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: Compliance Course, Corporate Training, Learner Behaviours, xAPI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 521

Authors: Naushad Mamode Khan

Abstract:

The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood-based estimating methodology. The joint generalized quasi-likelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill-conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQL-III) that is based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: Longitudinal, Com-Poisson, Ill-conditioned, INAR(1), GLMS, GQL.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1732

Authors: Ritu Vijay, Rekha Govil

Abstract:

The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1608

Authors: S. Oujdi, H. Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 Algorithm, Decision trees, S-CART, Spatial data mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2939

Authors: Michael Lissack

Abstract:

We depend upon explanation in order to “make sense" out of our world. And, making sense is all the more important when dealing with change. But, what happens if our explanations are wrong? This question is examined with respect to two types of explanatory model. Models based on labels and categories we shall refer to as “representations." More complex models involving stories, multiple algorithms, rules of thumb, questions, ambiguity we shall refer to as “compressions." Both compressions and representations are reductions. But representations are far more reductive than compressions. Representations can be treated as a set of defined meanings – coherence with regard to a representation is the degree of fidelity between the item in question and the definition of the representation, of the label. By contrast, compressions contain enough degrees of freedom and ambiguity to allow us to make internal predictions so that we may determine our potential actions in the possibility space. Compressions are explanatory via mechanism. Representations are explanatory via category. Managers are often confusing their evocation of a representation (category inclusion) as the creation of a context of compression (description of mechanism). When this type of explanatory error occurs, more errors follow. In the drive for efficiency such substitutions are all too often proclaimed – at the manager-s peril..

Keywords: Coherence, Emergence, Reduction, Model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1198

Authors: D. Karthikeyan, G. Balakrishnan

Abstract:

Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. Support Vector Regression (SVR) strategy is utilized to investigate age prediction. This paper depicts a feature extraction taking into account Gray Level Co-occurrence Matrix (GLCM), which can be utilized for robust face recognition framework. It applies GLCM operation to remove the face's features images and Active Appearance Models (AAMs) to assess the human age based on image. A fused feature technique and SVR with GA optimization are proposed to lessen the error in age estimation.

Keywords: Support vector regression, feature extraction, gray level co-occurrence matrix, active appearance models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1262

Authors: ChangWoo Lee, Young Kow Lee, Sung Jun Ban, SungHoo Choi, Sang Woo Kim

Abstract:

This paper suggests a new Affine Projection (AP) algorithm with variable data-reuse factor using the condition number as a decision factor. To reduce computational burden, we adopt a recently reported technique which estimates the condition number of an input data matrix. Several simulations show that the new algorithm has better performance than that of the conventional AP algorithm.

Keywords: Affine projection algorithm, variable data-reuse factor, condition number, convergence rate, misalignment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1506

Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

Abstract:

Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-destructive techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: Rebound, ultra-sonic pulse, penetration, ANN, NDT, regression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4324

Authors: Omer Ishag Eldai, Ahmed Hassan M. H. Ali, S. Raviraja

Abstract:

Web-based systems have become increasingly important due to the fact that the Internet and the World Wide Web have become ubiquitous, surpassing all other technological developments in our history. The Internet and especially companies websites has rapidly evolved in their scope and extent of use, from being a little more than fixed advertising material, i.e. a "web presences", which had no particular influence for the company's business, to being one of the most essential parts of the company's core business. Traditional software engineering approaches with process models such as, for example, CMM and Waterfall models, do not work very well since web system development differs from traditional development. The development differs in several ways, for example, there is a large gap between traditional software engineering designs and concepts and the low-level implementation model, many of the web based system development activities are business oriented (for example web application are sales-oriented, web application and intranets are content-oriented) and not engineering-oriented. This paper aims to introduce Increment Iterative extreme Programming (IIXP) methodology for developing web based systems. In difference to the other existence methodologies, this methodology is combination of different traditional and modern software engineering and web engineering principles.

Keywords: Web based systems, Web engineering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1808

Authors: Hironori Karachi, Haruka Yamashita

Abstract:

Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: Data science, non-negative matrix factorization, missing data, quality of services.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 390

Authors: Gururaj S Punekar, N K Kishore Senior, H S Y Shastry

Abstract:

Charge Simulation Method (CSM) is one of the very widely used numerical field computation technique in High Voltage (HV) engineering. The high voltage fields of varying non uniformities are encountered in practice. CSM programs being case specific, the simulation accuracies heavily depend on the user (programmers) experience. Here is an effort to understand CSM errors and evolve some guidelines to setup accurate CSM models, relating non uniformities with assignment factors. The results are for the six-point-charge model of sphere-plane gap geometry. Using genetic algorithm (GA) as tool, optimum assignment factors at different non uniformity factors for this model have been evaluated and analyzed. It is shown that the symmetrically placed six-point-charge models can be good enough to set up CSM programs with potential errors less than 0.1% when the field non uniformity factor is greater than 2.64 (field utilization factor less than 52.76%).

Keywords: Assignment factor, Charge Simulation Method, High Voltage, Numerical field computation, Non uniformity factor, Simulation errors.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2001

Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian

Abstract:

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Keywords: Clustering, Data Mining, Fuzzy Cognitive Map(FCM), Learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1971

Authors: K. N. Dinesh Babu, G. R. Manjunatha, R. Ramaprabha, V. Rajini, M. V. Gopalan

Abstract:

In this paper, monitoring and control of tap changer mechanism of a transformer implementation in an Intelligent Electronic Device (IED) is discussed. It has been a custom for decades to provide a separate panel for on load tap changer control for monitoring the tap position. However, this facility cannot either record or transfer the information to remote control centers. As there is a technology shift towards the smart grid protection and control standards, the need for implementing remote control and monitoring has necessitated the implementation of this feature in numerical relays. This paper deals with the programming, settings and logic implementation which is applicable to both IEC 61850 compatible and non-compatible IEDs thereby eliminating the need for separate tap changer control equipment. The monitoring mechanism has been implemented in a 28MVA, 110 /6.9kV transformer with 16 tap position with GE make T60 IED at Ultratech cement limited Gulbarga, Karnataka and is in successful service.

Keywords: Transformer protection, tap changer control, tap position monitoring, on load tap changer, intelligent electronic device (IED).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3975

Authors: Ahmed S. Al-Abdulwahab

Abstract:

Generation system reliability assessment is an important task which can be performed using deterministic or probabilistic techniques. The probabilistic approaches have significant advantages over the deterministic methods. However, more complicated modeling is required by the probabilistic approaches. Power generation model is a basic requirement for this assessment. One form of the generation models is the well known capacity outage probability table (COPT). Different analytical techniques have been used to construct the COPT. These approaches require considerable mathematical modeling of the generating units. The unit-s models are combined to build the COPT which will add more burdens on the process of creating the COPT. Decimal to Binary Conversion (DBC) technique is widely and commonly applied in electronic systems and computing This paper proposes a novel utilization of the DBC to create the COPT without engaging in analytical modeling or time consuming simulations. The simple binary representation , “0 " and “1 " is used to model the states o f generating units. The proposed technique is proven to be an effective approach to build the generation model.

Keywords: Decimal to Binary, generation, reliability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1992

Authors: Lari Kela

Abstract:

An adaptive Helmholtz resonator was designed and adapted to hydraulics. The resonator was controlled by open- and closed-loop controls so that 20 dB attenuation of the peak-to-peak value of the pulsating pressure was maintained. The closed-loop control was noted to be better, albeit it was slower because of its low pressure and temperature variation, which caused variation in the effective bulk modulus of the hydraulic system. Low-pressure hydraulics contains air, which affects the stiffness of the hydraulics, and temperature variation changes the viscosity of the oil. Thus, an open-loop control loses its efficiency if a condition such as temperature or the amount of air changes after calibration. The instability of the low-pressure hydraulic system reduced the operational frequency range of the Helmholtz resonator when compared with the results of an analytical model. Different dampers for hydraulics are presented. Then analytical models of a hydraulic pipe and a hydraulic pipe with a Helmholtz resonator are presented. The analytical models are based on the wave equation of sound pressure. Finally, control methods and the results of experiments are presented.

Keywords: adaptive, damper, hydraulics, pressure, pulsating

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4268

Authors: Asaiel Alohaly

Abstract:

A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-Owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised while the government retains significant control or holds a majority of shares. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. This research argues for the state model, which proceeds from an understanding of the institutionally embedded characteristics of hybrid companies, where the government as a shareholder, is either a majority of the total shares, or has been granted power based on the rule of law; the company bylaws.

Keywords: Corporate governance, control, shareholders, state model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1206

Authors: Naushad Mamode Khan, Cheika Jahangeer, Maleika Heenaye-Mamode Khan

Abstract:

Breastfeeding is an important concept in the maternal life of a woman. In this paper, we focus on exclusive breastfeeding. Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. This type of breastfeeding is very important during the first six months because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in Mauritius, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we give an overview of exclusive breastfeeding in Mauritius and the factors influencing it. We further analyze the local practices of exclusive breastfeeding using the Generalized Poisson regression model and the negative-binomial model since the data are over-dispersed.

Keywords: Exclusive breast feeding, regression model, generalized poisson, negative binomial.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1546