Search results for: computer aided prediction.

Authors: Caihong Su

Abstract:

Transition prediction of boundary layers has always been an important problem in fluid mechanics both theoretically and practically, yet notwithstanding the great effort made by many investigators, there is no satisfactory answer to this problem. The most popular method available is so-called e-N method which is heavily dependent on experiments and experience. The author has proposed improvements to the e-N method, so to reduce its dependence on experiments and experience to a certain extent. One of the key assumptions is that transition would occur whenever the velocity amplitude of disturbance reaches 1-2% of the free stream velocity. However, the reliability of this assumption needs to be verified. In this paper, transition prediction on a flat plate is investigated by using both the improved e-N method and the parabolized stability equations (PSE) methods. The results show that the transition locations predicted by both methods agree reasonably well with each other, under the above assumption. For the supersonic case, the critical velocity amplitude in the improved e-N method should be taken as 0.013, whereas in the subsonic case, it should be 0.018, both are within the range 1-2%.

Keywords: Boundary layer, e-N method, PSE, Transition

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1462

Authors: M. S. Abdelwahed, M. A. El-Baz, T. T. El-Midany

Abstract:

this paper aims to provide an approach to predict the performance of the product produced after multi-stages of manufacturing processes, as well as the assembly. Such approach aims to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. The approach is guided by a six-sigma methodology to obtain improved performance. In this paper a case study of the manufacture of a hermetic reciprocating compressor is presented. The application of artificial neural networks (ANNs) technique is introduced to improve performance prediction within this manufacturing environment. The results demonstrate that the approach predicts accurately and effectively.

Keywords: Artificial neural networks, Reciprocating compressor manufacturing, Performance prediction, Quality improvement

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1740

Authors: M. V. G. Silva, J. Gazzola, I. M. Dal Fabbro, A. C. L. Lino

Abstract:

Computer aided design accounts with the support of parametric software in the design of machine components as well as of any other pieces of interest. The complexities of the element under study sometimes offer certain difficulties to computer design, or ever might generate mistakes in the final body conception. Reverse engineering techniques are based on the transformation of already conceived body images into a matrix of points which can be visualized by the design software. The literature exhibits several techniques to obtain machine components dimensional fields, as contact instrument (MMC), calipers and optical methods as laser scanner, holograms as well as moiré methods. The objective of this research work was to analyze the moiré technique as instrument of reverse engineering, applied to bodies of nom complex geometry as simple solid figures, creating matrices of points. These matrices were forwarded to a parametric software named SolidWorks to generate the virtual object. Volume data obtained by mechanical means, i.e., by caliper, the volume obtained through the moiré method and the volume generated by the SolidWorks software were compared and found to be in close agreement. This research work suggests the application of phase shifting moiré methods as instrument of reverse engineering, serving also to support farm machinery element designs.

Keywords: Reverse engineering, Moiré technique, three dimensional image generation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3414

Authors: H. Özkan

Abstract:

In this study, a new and fast algorithm for Ascending Aorta (AscA) and Descending Aorta (DesA) segmentation is presented using Computed Tomography Angiography images. This process is quite important especially at the detection of aortic plaques, aneurysms, calcification or stenosis. The applied method has been carried out at four steps. At first step, lung segmentation is achieved. At the second one, Mediastinum Region (MR) is detected to use in the segmentation. At the third one, images have been applied optimal threshold and components which are outside of the MR were removed. Lastly, identifying and segmentation of AscA and DesA have been carried out. The performance of the applied method is found quite well for radiologists and it gives enough results to the surgeries medically.

Keywords: Ascending aorta (AscA), Descending aorta (DesA), Computed tomography angiography (CTA), Computer aided detection (CAD), Segmentation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1791

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 568

Authors: Somayeh Tourani, Alireza Behvandi

Abstract:

The peng-Robinson (PR), a cubic equation of state (EoS), is extended to polymers by using a single set of energy (A1, A2, A3) and co-volume (b) parameters per polymer fitted to experimental volume data. Excellent results for the volumetric behavior of the 11 polymer up to 2000 bar pressure are obtained. The EoS is applied to the correlation and prediction of Henry constants in polymer solutions comprising three polymer and many nonpolar and polar solvents, including supercritical gases. The correlation achieved with two adjustable parameter is satisfactory compared with the experimental data. As a result, the present work provides a simple and useful model for the prediction of Henry's constant for polymer containing systems including those containing polar, nonpolar and supercritical fluids.

Keywords: Equation of state, Henry's constant, Peng-Robinson, polymer solution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2079

Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

Abstract:

When it comes to last, it is regarded as the critical foundation of shoe design and development. A computer aided methodology for various last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then with the minimum energy for revision of surface continuity, the surface reconstruction of last is rebuilt by the feature curves of the scanned last. When the surface reconstruction of last is completed, the weighted arithmetic mean method is applied to the computation on the shape morphing for the control mesh of last, thus 3D last form of different sizes is generated from its original form feature with functions remained. In the end, the result of this study is applied to an application for 3D last reconstruction system. The practicability of the proposed methodology is verified through later case studies.

Keywords: Reverse engineering, Surface reconstruction, Surface continuity, Shape morphing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1710

Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

Abstract:

The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5590

Authors: Lee P. Leon, Raymond Charles

Abstract:

This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: Aggregate angularity, asphalt concrete, permanent deformation, rutting prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2035

Authors: Rahib Abiyev, Vasif H. Abiyev, C. Ardil

Abstract:

In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, neuro-fuzzy prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1946

Authors: Guy Leshem, Ya'acov Ritov

Abstract:

Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.

Keywords: Machine Learning, Boosting, Classification, TrafficCongestion, Data Collecting, Magnetic Loop Detectors, SignalizedIntersections, Traffic Signal Timing Optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3854

Authors: EL-Sayed M. M. EL-Refaie, Mohamed R. Salem, Wael A. Ahmed

Abstract:

Power systems and transformer are intrinsic apparatus, therefore its reliability and safe operation is important to determine their operation conditions, and the industry uses quality control tests in the insulation design of oil filled transformers. Hence the service period effect on AC dielectric strength is significant. The effect of aging on transformer oil physical, chemical and electrical properties was studied using the international testing methods for the evaluation of transformer oil quality. The study was carried out on six transformers operate in the field and for monitoring periods over twenty years. The properties which are strongly time dependent were specified and those which have a great impact on the transformer oil acidity, breakdown voltage and dissolved gas analysis were defined. Several tests on the transformers oil were studied to know the time of purifying or changing it, moreover prediction of the characteristics of it under different operation conditions.

Keywords: Dissolved Gas Analysis, Prediction, Purifying and Changing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3677

Authors: A. A. Pawar, R. R. Kulkarni

Abstract:

For numerical prediction of the NOX in the exhaust of a compression ignition engine a model was developed by considering the parameter equivalence ratio. This model was validated by comparing the predicted results of NOX with experimental ones. The ultimate aim of the work was to access the applicability, robustness and performance of the improved NOX model against other NOX models.

Keywords: Biodiesel fueled engine, equivalence ratio, Compression ignition engine, exhausts gas temperature, NOX formation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2040

Authors: Anwar Jarndal

Abstract:

In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design & modeling, neural networks, genetic optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1598

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: Academic performance prediction system, prediction model, educational data mining, dominant factors, feature selection methods, student performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 908

Authors: Baeza S. Roberto

Abstract:

The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes is included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: Neural network, dry relaxation, knitting, linear regression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1720

Authors: Muhammad Ridhuan Tony Lim Abdullah, Zulqarnain Abu Bakar, Razol Mahari Ali, Ibrahima Faye, Hilmi Hasan

Abstract:

This paper describes a research project on Year 3 primary school students in Malaysia in their use of computer-based video game to enhance learning of multiplication facts (tables) in the Mathematics subject. This study attempts to investigate whether video games could actually contribute to positive effect on children-s learning or otherwise. In conducting this study, the researchers assume a neutral stand in the investigation as an unbiased outcome of the study would render reliable response to the impact of video games in education which would contribute to the literature of technology-based education as well as impact to the pedagogical aspect of formal education. In order to conduct the study, a subject (Mathematics) with a specific topic area in the subject (multiplication facts) is chosen. The study adopts a causal-comparative research to investigate the impact of the inclusion of a computer-based video game designed to teach multiplication facts to primary level students. Sample size is 100 students divided into two i.e., A: conventional group and B conventional group aided by video games. The conventional group (A) would be taught multiplication facts (timetables) and skills conventionally. The other group (B) underwent the same lessons but with supplementary activity: a computer-based video game on multiplication which is called Timez-Attack. Analysis of marks accrued from pre-test will be compared to post- test using comparisons of means, t tests, and ANOVA tests to investigate the impact of computer games as an added learning activity. The findings revealed that video games as a supplementary activity to classroom learning brings significant and positive effect on students- retention and mastery of multiplication tables as compared to students who rely only upon formal classroom instructions.

Keywords: Technology for education, Gaming for education, Computer-based video games, Cognitive learning

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4194

Authors: Wen-liang Chen, Peng Wei, Yidong Bao

Abstract:

This paper presents a linear-elastic finite element method based flattening algorithm for three dimensional triangular surfaces. First, an intrinsic characteristic preserving method is used to obtain the initial developing graph, which preserves the angles and length ratios between two adjacent edges. Then, an iterative equation is established based on linear-elastic finite element method and the flattening result with an equilibrium state of internal force is obtained by solving this iterative equation. The results show that complex surfaces can be dealt with this proposed method, which is an efficient tool for the applications in computer aided design, such as mould design.

Keywords: Triangular mesh, surface flattening, finite elementmethod, linear-elastic deformation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3116

Authors: Dong Wook Lee, Adrian Mistreanu

Abstract:

The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: Computer Aided Engineering, CAE, containment analysis, Finite Element Analysis, FEA, impact analysis, penetration analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 471

Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

Abstract:

Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: Cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 717

Authors: Marine Segui, Ruxandra Mihaela Botez

Abstract:

OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: Aerodynamic, coefficient, cruise, improving, longitudinal, OpenVSP, solver, time.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385

Authors: Ashish R. Tanna, Hiren H. Joshi

Abstract:

The mineral having chemical compositional formula MgAl2O4 is called “spinel". The ferrites crystallize in spinel structure are known as spinel-ferrites or ferro-spinels. The spinel structure has a fcc cage of oxygen ions and the metallic cations are distributed among tetrahedral (A) and octahedral (B) interstitial voids (sites). The X-ray diffraction (XRD) intensity of each Bragg plane is sensitive to the distribution of cations in the interstitial voids of the spinel lattice. This leads to the method of determination of distribution of cations in the spinel oxides through XRD intensity analysis. The computer program for XRD intensity analysis has been developed in C language and also tested for the real experimental situation by synthesizing the spinel ferrite materials Mg0.6Zn0.4AlxFe2- xO4 and characterized them by X-ray diffractometry. The compositions of Mg0.6Zn0.4AlxFe2-xO4(x = 0.0 to 0.6) ferrites have been prepared by ceramic method and powder X-ray diffraction patterns were recorded. Thus, the authenticity of the program is checked by comparing the theoretically calculated data using computer simulation with the experimental ones. Further, the deduced cation distributions were used to fit the magnetization data using Localized canting of spins approach to explain the “recovery" of collinear spin structure due to Al3+ - substitution in Mg-Zn ferrites which is the case if A-site magnetic dilution and non-collinear spin structure. Since the distribution of cations in the spinel ferrites plays a very important role with regard to their electrical and magnetic properties, it is essential to determine the cation distribution in spinel lattice.

Keywords: Spinel ferrites, Localized canting of spins, X-ray diffraction, Programming in Borland C.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3735

Authors: Tsun-Hui Huang, Shyue-Cheng Yang, Chiou-Fen Shieh

Abstract:

In this paper, a nonlinear constitutive law and a curve fitting, two relationships between the stress-strain and the shear stress-strain for sandstone material were used to obtain a second-order polynomial constitutive equation. Based on the established polynomial constitutive equations and Newton’s second law, a mathematical model of the non-homogeneous nonlinear wave equation under an external pressure was derived. The external pressure can be assumed as an impulse function to simulate a real earthquake source. A displacement response under nonlinear two-dimensional wave equation was determined by a numerical method and computer-aided software. The results show that a suit pressure in the sandstone generates the phenomenon of stress solitary waves.

Keywords: Polynomial constitutive equation, solitary.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1625

Authors: Nor Azuana Ramli, Mohd Tahir Ismail, Hooy Chee Wooi

Abstract:

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we take the Euclidean distance and the Manhattan as a consideration. For the comparison, we employ three other methods which are logistic regression analysis (logit), back-propagation neural network (NN) and sequential minimal optimization (SMO). The analysis using datasets from 8 countries and 13 macro-economic indicators for each country shows that the proposed k-NN method with k = 4 and Manhattan distance performs better than the other methods.

Keywords: Currency crisis, k-nearest neighbour method, logit, neural network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2253

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: Image processing technique, Feature detections, Surface registrations, Capturing multi-view images, Production costs, and Manufacturing processes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915

Authors: Stephen C. W. Kong

Abstract:

The use of 3D computer-aided design (CAD) models to support construction project planning has been increasing in the previous year. 3D CAD models reveal more planning ideas by visually showing the construction site environment in different stages of the construction process. Using 3D CAD models together with scheduling software to prepare construction plan can identify errors in process sequence and spatial arrangement, which is vital to the success of a construction project. A number of 4D (3D plus time) CAD tools has been developed and utilized in different construction projects due to the awareness of their importance. Virtual prototyping extends the idea of 4D CAD by integrating more features for simulating real construction process. Virtual prototyping originates from the manufacturing industry where production of products such as cars and airplanes are virtually simulated in computer before they are built in the factory. Virtual prototyping integrates 3D CAD, simulation engine, analysis tools (like structural analysis and collision detection), and knowledgebase to streamline the whole product design and production process. In this paper, we present the application of a virtual prototyping software which has been used in a few construction projects in Hong Kong to support construction project planning. Specifically, the paper presents an implementation of virtual prototyping in a residential building project in Hong Kong. The applicability, difficulties and benefits of construction virtual prototyping are examined based on this project.

Keywords: construction project planning, prefabrication, simulation, virtual prototyping.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2769

Authors: Chyn Liaw, Chun-Wei Tung, Shinn-Jang Ho, Shinn-Ying Ho

Abstract:

The γ-turns play important roles in protein folding and molecular recognition. The prediction and analysis of γ-turn types are important for both protein structure predictions and better understanding the characteristics of different γ-turn types. This study proposed a physicochemical property-based decision tree (PPDT) method to interpretably predict γ-turn types. In addition to the good prediction performance of PPDT, three simple and human interpretable IF-THEN rules are extracted from the decision tree constructed by PPDT. The identified informative physicochemical properties and concise rules provide a simple way for discriminating and understanding γ-turn types.

Keywords: Classification and regression tree (CART), γ-turn, Physicochemical properties, Protein secondary structure.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1507

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

Abstract:

The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: Comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1453

Authors: Ö.F. Ursavas, H. Karal

Abstract:

In this study it is aimed to determine the level of preservice teachers- computer phobia. Whether or not computer phobia meaningfully varies statistically according to gender and computer experience has been tested in the study. The study was performed on 430 pre-service teachers at the Education Faculty in Rize/Turkey. Data in the study were collected through the Computer Phobia Scale consisting of the “Personal Knowledge Questionnaire", “Computer Anxiety Rating Scale", and “Computer Thought Survey". In this study, data were analyzed with statistical processes such as t test, and correlation analysis. According to results of statistical analyses, computer phobia of male pre-service teachers does not statistically vary depending on their gender. Although male preservice teachers have higher computer anxiety scores, they have lower computer thought scores. It was also observed that there is a negative and intensive relation between computer experience and computer anxiety. Meanwhile it was found out that pre-service teachers using computer regularly indicated lower computer anxiety. Obtained results were tried to be discussed in terms of the number of computer classes in the Education Faculty curriculum, hours of computer class and the computer availability of student teachers.

Keywords: Computer phobia, computer anxiety, computer thought, pre-service teachers.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2181

Authors: Kleanthis Prekas, Maria Rangoussi, Savvas Vassiliadis, George Prekas

Abstract:

Intelligent tutoring systems constitute an evolution of computer-aided educational software. We present here the modules of an intelligent tutoring system for Automatic Control, developed in our department. Through the software application developed,students can perform complete automatic control laboratory experiments, either over the departmental local area network or over the Internet. Monitoring of access to the system (local as well as international), along with student performance statistics, has yielded strongly encouraging results (as of fall 2004), despite the advanced technical content of the presented paradigm, thus showing the potential of the system developed for education and for training.

Keywords: Automatic control, tutoring system, Internet access, laboratory experiments.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1611