Search results for: RMS error
858 Effects of International Trade on Economic Growth
Authors: Tanimola Kazeem Abiodun
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In the paper, attempt was made to investigate the impact of international trade on economic growth at the disaggregate level both from the theoretical and economic angle. The study in its contribution examines this impact at the disaggregated level. To this end, a hypothesis was formulated to investigate the short ?run and long run impact of international trade on growth in the country. In the econometrics investigation that follow, international trade was disaggregated to export and imports and their short run and long run effect on growth was examined. Also, the aggregate international trade was also investigated to see the long run effects of its own growth. The results of the findings indicate that; both export and import impact significantly to growth in the short run. The long-run impact of export on growth was found to be positive, significant and stable both. Engle-Granger co integration test and error correlation mechanism were applied to these long run relationships. For the import, while the short run was found to be positive and significant on its impact on growth, the long run relationship was found to be negative but not significant. Therefore, it is thus recommended among others that the country should engage more on export promotion drives.Keywords: international trade, disaggregated, import, export, econometrics, trade, economic growth, foreign trade, import, export
Procedia PDF Downloads 404857 Crack Width Evaluation for Flexural RC Members with Axial Tension
Authors: Sukrit Ghorai
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Proof of controlling crack width is a basic condition for securing suitable performance in serviceability limit state. The cracking in concrete can occur at any time from the casting of time to the years after the concrete has been set in place. Most codes struggle with offering procedure for crack width calculation. There is lack in availability of design charts for designers to compute crack width with ease. The focus of the study is to utilize design charts and parametric equations in calculating crack width with minimum error. The paper contains a simplified procedure to calculate crack width for reinforced concrete (RC) sections subjected to bending with axial tensile force following the guidelines of Euro code [DS EN-1992-1-1 & DS EN-1992-1-2]. Numerical examples demonstrate the application of the suggested procedure. Comparison with parallel analytical tools support the validity of result and show the percentage deviation of crack width in both the procedures. The technique is simple, user-friendly and ready to evolve for a greater spectrum of section sizes and materials.Keywords: concrete structures, crack width calculation, serviceability limit state, structural design, bridge engineering
Procedia PDF Downloads 378856 Statistical Classification, Downscaling and Uncertainty Assessment for Global Climate Model Outputs
Authors: Queen Suraajini Rajendran, Sai Hung Cheung
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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.Keywords: statistical downscaling, global climate model, climate change, uncertainty
Procedia PDF Downloads 362855 The Ability of Forecasting the Term Structure of Interest Rates Based on Nelson-Siegel and Svensson Model
Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović
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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve
Procedia PDF Downloads 317854 Theoretical Studies on the Formation Constant, Geometry, Vibrational Frequencies and Electronic Properties Dinuclear Molybdenum Complexes
Authors: Mahboobeh Mohadeszadeh, Behzad Padidaran Moghaddam
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In order to measuring dinuclear molybdenum complexes formation constant First,the reactants and the products were optimized separately and then, their frequencies were measured. In next level , with using Hartree-fock (HF) and density functional theory (DFT) methods ,Theoretical studies on the geometrical parameters, electronic properties and vibrational frequencies of dinuclear molybdenum complexes [C40H44Mo2N2O20] were investigated . These calculations were performed with the B3LYP, BPV86, B3PW91 and HF theoretical method using the LANL2DZ (for Mo’s) + 6-311G (for others) basis sets. To estimate the error rate between theoretical data and experimental data, RSquare , SError and RMS values that according with the theoretical and experimental parameters found out DFT methods has more integration with experimental data compare to HF methods. In addition, through electron specification of compounds, the percentage of atomic orbital’s attendance in making molecular orbital’s, atoms electrical charge, the sustainable energy resulting and also HOMO and LUMO orbital’s energy achieved.Keywords: geometrical parameters, hydrogen bonding, electronic properties, vibrational frequencies
Procedia PDF Downloads 266853 Hybrid Wavelet-Adaptive Neuro-Fuzzy Inference System Model for a Greenhouse Energy Demand Prediction
Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani
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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse
Procedia PDF Downloads 78852 Detection of Image Blur and Its Restoration for Image Enhancement
Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad
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Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.Keywords: image enhancement, motion analysis, motion detection, motion estimation
Procedia PDF Downloads 279851 Performance Analysis and Comparison of Various 1-D and 2-D Prime Codes for OCDMA Systems
Authors: Gurjit Kaur, Shashank Johri, Arpit Mehrotra
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In this paper we have analyzed and compared the performance of various coding schemes. The basic ID prime sequence codes are unique in only dimension i.e. time slots whereas 2D coding techniques are not unique by their time slots but with their wavelengths also. In this research we have evaluated and compared the performance of 1D and 2D coding techniques constructed using prime sequence coding pattern for OCDMA system on a single platform. Results shows that 1D Extended Prime Code (EPC) can support more number of active users compared to other codes but at the expense of larger code length which further increases the complexity of the code. Modified Prime Code (MPC) supports lesser number of active users at λc=2 but it has a lesser code length as compared to 1D prime code. Analysis shows that 2D prime code supports lesser number of active users than 1D codes but they are having large code family and are the most secure codes compared to other codes. The performance of all these codes is analyzed on basis of number of active users supported at a Bit Error Rate (BER) of 10-9.Keywords: CDMA, OCDMA, BER, OOC, PC, EPC, MPC, 2-D PC/PC, λc, λa
Procedia PDF Downloads 501850 Empirical Modeling of Air Dried Rubberwood Drying System
Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit
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Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (R²), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (R² = 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.Keywords: empirical models, rubberwood, moisture ratio, hot air drying
Procedia PDF Downloads 259849 The Impact of Corporate Social Responsibility Information Disclosure on the Accuracy of Analysts' Earnings Forecasts
Authors: Xin-Hua Zhao
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In recent years, the growth rate of social responsibility reports disclosed by Chinese corporations has grown rapidly. The economic effects of the growing corporate social responsibility reports have become a hot topic. The article takes the chemical listed engineering corporations that disclose social responsibility reports in China as a sample, and based on the information asymmetry theory, examines the economic effect generated by corporate social responsibility disclosure with the method of ordinary least squares. The research is conducted from the perspective of analysts’ earnings forecasts and studies the impact of corporate social responsibility information disclosure on improving the accuracy of analysts' earnings forecasts. The results show that there is a statistically significant negative correlation between corporate social responsibility disclosure index and analysts’ earnings forecast error. The conclusions confirm that enterprises can reduce the asymmetry of social and environmental information by disclosing social responsibility reports, and thus improve the accuracy of analysts’ earnings forecasts. It can promote the effective allocation of resources in the market.Keywords: analysts' earnings forecasts, corporate social responsibility disclosure, economic effect, information asymmetry
Procedia PDF Downloads 149848 ESL Students’ Engagement with Written Corrective Feedback
Authors: Khaled Karim
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Although a large number of studies have examined the effectiveness of written corrective feedback (WCF) in L2 writing, very few studies have investigated students’ attitudes towards the feedback and their perspectives regarding the usefulness of different types of feedback. Using prompted stimulated recall interviews, this study investigated ESL students’ perceptions and attitudes towards the CF they received as well as their preferences and reactions to the corrections. 24 ESL students first received direct (e.g., providing target forms after crossing out erroneous forms) and indirect (e.g., underlining and underline+metalinguistic) CF on four written tasks and then participated in an interview with the researcher. The analysis revealed that both direct and indirect CF were judged to be useful strategies for correction but in different ways. Underline only CF helped them think about the nature and type of the errors they made while metalinguistic CF was useful as it provided clues about the nature and type of the errors. Most participants indicated that indirect correction needed sufficient prior knowledge of the form to be effective. The majority of the students found the combination of underlining with metalinguistic information as the most effective method of providing feedback. Detailed findings will be presented, and pedagogical implications of the study will be discussed.Keywords: ESL writing, error correction, feedback, written corrective feedback
Procedia PDF Downloads 228847 Research on Robot Adaptive Polishing Control Technology
Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang
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Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. It is more and more necessary to replace manual polishing with robot polishing. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a new type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model shows that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.Keywords: robot polishing, force feedback, impedance control, adaptive control
Procedia PDF Downloads 191846 Presenting a Model for Predicting the State of Being Accident-Prone of Passages According to Neural Network and Spatial Data Analysis
Authors: Hamd Rezaeifar, Hamid Reza Sahriari
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Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.Keywords: accident, data mining, neural network, GIS
Procedia PDF Downloads 43845 Application of Hybrid Honey Bees Mating Optimization Algorithm in Multiuser Detection of Wireless Communication Systems
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Wireless communication systems have changed dramatically and shown spectacular evolution over the past two decades. These radio technologies are engaged in a quest endless high-speed transmission coupled to a constant need to improve transmission quality. Various radio communication systems being developed use code division multiple access (CDMA) technique. This work analyses a hybrid honey bees mating optimization algorithm (HBMO) applied to multiuser detection (MuD) in CDMA communication systems. The HBMO is a swarm-based optimization algorithm, which simulates the mating process of real honey bees. We apply a hybridization of HBMO with simulated annealing (SA) in order to improve the solution generated by the HBMO. Simulation results show that the detection based on Hybrid HBMO, in term of bit error rate (BER), is viable option when compared with the classic detectors from literature under Rayleigh flat fading channel.Keywords: BER, DS-CDMA multiuser detection, genetic algorithm, hybrid HBMO, simulated annealing
Procedia PDF Downloads 423844 Reduction of Multiple User Interference for Optical CDMA Systems Using Successive Interference Cancellation Scheme
Authors: Tawfig Eltaif, Hesham A. Bakarman, N. Alsowaidi, M. R. Mokhtar, Malek Harbawi
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In Commonly, it is primary problem that there is multiple user interference (MUI) noise resulting from the overlapping among the users in optical code-division multiple access (OCDMA) system. In this article, we aim to mitigate this problem by studying an interference cancellation scheme called successive interference cancellation (SIC) scheme. This scheme will be tested on two different detection schemes, spectral amplitude coding (SAC) and direct detection systems (DS), using partial modified prime (PMP) as the signature codes. It was found that SIC scheme based on both SAC and DS methods had a potential to suppress the intensity noise, that is to say, it can mitigate MUI noise. Furthermore, SIC/DS scheme showed much lower bit error rate (BER) performance relative to SIC/SAC scheme for different magnitude of effective power. Hence, many more users can be supported by SIC/DS receiver system.Keywords: optical code-division multiple access (OCDMA), successive interference cancellation (SIC), multiple user interference (MUI), spectral amplitude coding (SAC), partial modified prime code (PMP)
Procedia PDF Downloads 516843 Blind Watermarking Using Discrete Wavelet Transform Algorithm with Patchwork
Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting
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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark
Procedia PDF Downloads 264842 Towards an Intelligent Ontology Construction Cost Estimation System: Using BIM and New Rules of Measurement Techniques
Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah
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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or under-estimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improves accuracies. This requires standard measurement methods to be structured in ontologically and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.Keywords: BIM, construction projects, cost estimation, NRM, ontology
Procedia PDF Downloads 544841 Drying Kinetics of Vacuum Dried Beef Meat Slices
Authors: Elif Aykin Dincer, Mustafa Erbas
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The vacuum drying behavior of beef slices (10 x 4 x 0.2 cm3) was experimentally investigated at the temperature of 60, 70, and 80°C under 25 mbar ultimate vacuum pressure and the mathematical models (Lewis, Page, Midilli, Two-term, Wangh and Singh and Modified Henderson and Pabis) were used to fit the vacuum drying of beef slices. The increase in drying air temperature resulted in a decrease in drying time. It took approximately 206, 180 and 157 min to dry beef slices from an initial moisture content to a final moisture content of 0.05 kg water/kg dry matter at 60, 70 and 80 °C of vacuum drying, respectively. It is also observed that the drying rate increased with increasing drying temperature. The coefficients (R2), the reduced chi-square (x²) and root mean square error (RMSE) values were obtained by application of six models to the experimental drying data. The best model with the highest R2 and, the lowest x² and RMSE values was selected to describe the drying characteristics of beef slices. The Page model has shown a better fit to the experimental drying data as compared to other models. In addition, the effective moisture diffusivities of beef slices in the vacuum drying at 60 - 80 °C varied in the range of 1.05 – 1.09 x 10-10 m2/s. Consequently, this results can be used to simulate vacuum drying process of beef slices and improve efficiency of the drying process.Keywords: beef slice, drying models, effective diffusivity, vacuum
Procedia PDF Downloads 283840 Digital Image Steganography with Multilayer Security
Authors: Amar Partap Singh Pharwaha, Balkrishan Jindal
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In this paper, a new method is developed for hiding image in a digital image with multilayer security. In the proposed method, the secret image is encrypted in the first instance using a flexible matrix based symmetric key to add first layer of security. Then another layer of security is added to the secret data by encrypting the ciphered data using Pythagorean Theorem method. The ciphered data bits (4 bits) produced after double encryption are then embedded within digital image in the spatial domain using Least Significant Bits (LSBs) substitution. To improve the image quality of the stego-image, an improved form of pixel adjustment process is proposed. To evaluate the effectiveness of the proposed method, image quality metrics including Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), entropy, correlation, mean value and Universal Image Quality Index (UIQI) are measured. It has been found experimentally that the proposed method provides higher security as well as robustness. In fact, the results of this study are quite promising.Keywords: Pythagorean theorem, pixel adjustment, ciphered data, image hiding, least significant bit, flexible matrix
Procedia PDF Downloads 329839 A Greedy Alignment Algorithm Supporting Medication Reconciliation
Authors: David Tresner-Kirsch
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Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm
Procedia PDF Downloads 275838 Sectoral Energy Consumption in South Africa and Its Implication for Economic Growth
Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari
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South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output
Procedia PDF Downloads 458837 A Visual Inspection System for Automotive Sheet Metal Chasis Parts Produced with Cold-Forming Method
Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir
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The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection
Procedia PDF Downloads 107836 A Sequential Approach for Random-Effects Meta-Analysis
Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya
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The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes
Procedia PDF Downloads 459835 Application of Support Vector Machines in Forecasting Non-Residential
Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut
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This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.Keywords: forecasting, non-residential, construction, support vector machines
Procedia PDF Downloads 429834 Sensitivity of the Estimated Output Energy of the Induction Motor to both the Asymmetry Supply Voltage and the Machine Parameters
Authors: Eyhab El-Kharashi, Maher El-Dessouki
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The paper is dedicated to precise assessment of the induction motor output energy during the unbalanced operation. Since many years ago and until now the voltage complex unbalance factor (CVUF) is used only to assess the output energy of the induction motor while this output energy for asymmetry supply voltage does not depend on the value of unbalanced voltage only but also on the machine parameters. The paper illustrates the variation of the two unbalance factors, complex voltage unbalance factor (CVUF) and impedance unbalance factor (IUF), with positive sequence voltage component, reveals that degree and manner of unbalance in supply voltage. From this point of view the paper delineates the current unbalance factor (CUF) to exactly reflect the output energy during unbalanced operation. The paper proceeds to illustrate the importance of using this factor in the multi-machine system to precise prediction of the output energy during the unbalanced operation. The use of the proposed unbalance factor (CUF) avoids the accumulation of the error due to more than one machine in the system which is expected if only the complex voltage unbalance factor (CVUF) is used.Keywords: induction motor, electromagnetic torque, voltage unbalance, energy conversion
Procedia PDF Downloads 553833 Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia
Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza
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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant
Procedia PDF Downloads 463832 Towards an Effective Approach for Modelling near Surface Air Temperature Combining Weather and Satellite Data
Authors: Nicola Colaninno, Eugenio Morello
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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing
Procedia PDF Downloads 189831 Macroeconomic Impact of Economic Growth on Unemployment: A Case of South Africa
Authors: Ashika Govender
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This study seeks to determine whether Okun’s Law is valid for the South African economy, using time series data for the period 2004 to 2014. The data were accessed from the South African Reserve Bank and Stats SA. The stationarity of the variables was analysed by applying unit root tests via the Augmented Dickey-Fuller test (ADF), the Phillips-Perron (PP) test, and the Kwiatkowski–Phillips–Schmidt–Shin test (KPSS) test. The study used an ordinary least square (OLS) model in analysing the dynamic version of Okun’s law. The Error Correction Model (ECM) was used to analyse the short-run impact of GDP growth on unemployment, as well as the speed of adjustment. The results indicate a short run and long run relationship between unemployment rate and GDP growth rate in period 2004q1-2014q4, suggesting that Okun’s law is valid for the South African economy. With a 1 percent increase in GDP, unemployment can decrease by 0.13 percent, ceteris paribus. The research culminates in important policy recommendations, highlighting the relationship between unemployment and economic growth in the spirit of the National Development Plan.Keywords: unemployment, economic growth, Okun's law, South Africa
Procedia PDF Downloads 266830 Prediction of the Mechanical Power in Wind Turbine Powered Car Using Velocity Analysis
Authors: Abdelrahman Alghazali, Youssef Kassem, Hüseyin Çamur, Ozan Erenay
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Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. This makes it suitable for electricity or mechanical generation in low-power applications such as individual domestic installations. Therefore, the primary purpose of this work was to investigate the relationship between the type of Savonius rotor and the torque and mechanical power generated. And it was to illustrate how the type of rotor might play an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy into mechanical energy to overcome load that rotates the main shaft. The predicted results based on theoretical analysis were compared with experimental results obtained from literature. The percentage of error between the two was approximately around 20%. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus.Keywords: mechanical power, torque, Savonius rotor, wind car
Procedia PDF Downloads 323829 Analysis of Production Forecasting in Unconventional Gas Resources Development Using Machine Learning and Data-Driven Approach
Authors: Dongkwon Han, Sangho Kim, Sunil Kwon
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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance
Procedia PDF Downloads 188