Search results for: radial error

Authors: Nattachote Rugthaicharoencheep

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This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

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Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

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Authors: Adil Balla Elkrail

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Visual MODFLOW computer codes were selected to simulate head distribution, calculate the groundwater budgets of the area, and evaluate the effect of external stresses on the groundwater head and to demonstrate how the groundwater model can be used as a comparative technique in order to optimize utilization of the groundwater resource. A conceptual model of the study area, aquifer parameters, boundary, and initial conditions were used to simulate the flow model. The trial-and-error technique was used to calibrate the model. The most important criteria used to check the calibrated model were Root Mean Square error (RMS), Mean Absolute error (AM), Normalized Root Mean Square error (NRMS) and mass balance. The maps of the simulated heads elaborated acceptable model calibration compared to observed heads map. A time length of eight years and the observed heads of the year 2004 were used for model prediction. The predictive simulation showed that the continuation of pumping will cause relatively high changes in head distribution and components of groundwater budget whereas, the low deficit computed (7122 m3/d) between inflows and outflows cannot create a significant drawdown of the potentiometric level. Hence, the area under consideration may represent a high permeability and productive zone and strongly recommended for further groundwater development.

Keywords: aquifers, model simulation, groundwater, calibrations, trail-and- error, prediction

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Authors: Nosheen Zareen Khan, Abdul Majeed Siddiqui, Muhammad Afzal Rana

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The steady flow of a second order fluid through constricted tube with slip velocity at wall is modeled and analyzed theoretically. The governing equations are simplified by implying no slip in radial direction. Based on Karman Pohlhausen procedure polynomial solution for axial velocity profile is presented. An expressions for pressure gradient, shear stress, separation and reattachment points and radial velocity are also calculated. The effect of slip and no slip velocity on velocity, shear stress, pressure gradient are discussed and depicted graphically. It is noted that when Reynolds number increases velocity of the fluid decreases in both slip and no slip conditions. It is also found that the wall shear stress, separation and reattachment points are strongly effected by Reynolds number.

Keywords: approximate solution, constricted tube, non-Newtonian fluids, Reynolds number

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Authors: N. Beit Saeid

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Cyclones are used in the field of air industrial gases pollution and control the pollution with centrifugal forces that is generated with spatial geometry of the cyclone. Their simple design, low capital and maintenance costs and adaptability to a wide range of operating conditions have made cyclones one of the most widely used industrial dust collectors. Their cost of operation is proportional to the fan energy required to overcome their pressure drop. Optimized geometry of outlet diffuser of the cyclones potentially could reduce exit pressure losses without affecting collection efficiency. Three rectangular outlets and a radial outlet with a variable opening had been analyzed on two cyclones. Pressure drop was investigated for inlet velocities from about 10 to 20 m s−1. The radial outlet reduced cyclone pressure drop by between 8.7 and 11.9 percent when its exit area was equal to the flow area of the cyclone vortex finder or gas exit. A simple payback based on avoided energy costs was estimated to be between 3600 and 5000 h, not including installation cost.

Keywords: cyclone, CFD, optimization, genetic algorithm

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Authors: Himayatullah Khan

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This study estimates supply response function of sugarcane in Pakistan from 1980-81 to 2012-13. The study uses co-integration approach and error correction mechanism. Sugarcane production, area and price series were tested for unit root using Augmented Dickey Fuller (ADF). The study found that these series were stationary at their first differenced level. Using the Augmented Engle-Granger test and Cointegrating Regression Durbin-Watson (CRDW) test, the study found that “production and price” and “area and price” were co-integrated suggesting that the two sets of time series had long-run or equilibrium relationship. The results of the error correction models for the two sets of series showed that there was disequilibrium in the short run there may be disequilibrium. The Engle-Granger residual may be thought of as the equilibrium error which can be used to tie the short-run behavior of the dependent variable to its long-run value. The Granger-Causality test results showed that log of price granger caused both the long of production and log of area whereas, the log of production and log of area Granger caused each other.

Keywords: co-integration, error correction mechanism, Granger-causality, sugarcane, supply response

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Authors: Okike Benjamin, Garba E. J. D.

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The researcher has developed a new encryption technique known as Merged Irregular Transposition Cipher. In this cipher method of encryption, a message to be encrypted is split into parts and each part encrypted separately. Before the encrypted message is transmitted to the recipient(s), the positions of the split in the encrypted messages could be swapped to ensure more security. This work seeks to develop a model by considering the split number, S and the average number of characters per split, L as the message under consideration is split from 2 through 10. Again, after developing the model, the error level in the model would be determined.

Keywords: merged irregular transposition, error level, model estimation, message splitting

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Authors: Rubaiyea Uddin, Rebecca Taylor, Emily Levesque

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The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated “reward” arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation.

Keywords: mice, radial arm maze, memory, spatial navigation, tactile cues, hippocampus, reward, sensory skills, Alzheimer's, neuro-degenerative diseases

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Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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With the evolution of the productive processes, demonstrated mainly by the presence every time larger of the irrigation and to crescent it disputes for water, accompanied by your shortage (distances every time larger), there is need to project facilities that can provide supply of water with larger speed and efficiency. Being like this, the presence of hydraulic pumps in an irrigation project or water supply for small communities, is of highest importance, and the knowledge of the fundamental parts to your good operation it deserves the due attention and care. Hydraulic pumps are machines of flow, whose function is to supply energy for the water, in order to press down her, through the conversion of mechanical energy of your originating from rotor a motor the combustion or of an electric motor. This way, the hydraulic pumps are had as generating hydraulic machines. The objective of this work was to project and to build a radial centrifugal pump for agricultural application in small communities.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigation

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Authors: Sanja Seljan, Ivan Dunđer

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The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: automatic machine translation, integrated language technologies, quality evaluation, speech recognition

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

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Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Hyeon-Kyo Lim, Tong-il Jang, Yong-Hee Lee

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As for any nuclear power plant, human error is one of the most dreaded factors that may result in unexpected accidents. Thus, for accident prevention, it is quite indispensable to analyze and to manage the influence of any factor which may raise the possibility of human errors. Among lots factors, stress has been reported to have significant influence on human performance. Stress level of a person may fluctuate over time. To handle the possibility over time, robust stress management program is required, especially in nuclear power plants. Therefore, to overcome the possibility of human errors, this study aimed to develop a stress management program as a part of Fitness-for-Duty (FFD) Program for the workers in nuclear power plants. The meaning of FFD might be somewhat different by research objectives, appropriate definition of FFD was accomplished in this study with special reference to human error prevention, and diverse stress factors were elicited for management of human error susceptibility. In addition, with consideration of conventional FFD management programs, appropriate tests and interventions were introduced over the whole employment cycle including selection and screening of workers, job allocation, job rotation, and disemployment as well as Employee-Assistance-Program (EAP). The results showed that most tools mainly concentrated their weights on common organizational factors such as Demands, Supports, and Relationships in sequence, which were referred as major stress factors.

Keywords: human error, accident prevention, work performance, stress, fatigue

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Authors: E. Marušić-Paloka, I. Pažanin, M. Prša

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Subject of this study is the stationary heat conduction problem through a pipe filled with incompressible viscous fluid. In previous work, we observed the existence and uniqueness theorems for the corresponding boundary-value problem and within we have taken into account the effects of the pipe's dilatation due to the temperature of the fluid inside of the pipe. The main difficulty comes from the fact that flow domain changes depending on the solution of the observed heat equation leading to a non-standard coupled governing problem. The goal of this work is to find solution estimate since the exact solution of the studied problem is not possible to determine. We use an asymptotic expansion in order of a small parameter which is presented as a heat expansion coefficient of the pipe's material. Furthermore, an error estimate is provided for the mentioned asymptotic approximation of the solution for inner area of the pipe. Close to the boundary, problem becomes more complex so different approaches are observed, mainly Theory of Perturbations and Separations of Variables. In view of that, error estimate for the whole approximation will be provided with additional software simulations of gotten situation.

Keywords: asymptotic analysis, dilated pipe, error estimate, heat conduction

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Authors: A. Abdikian

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A quantum breathing mode has been theatrically studied in quantum dusty plasma. By using linear quantum hydrodynamic model, not only the quantum dispersion relation of rotation mode but also void structure has been derived in the presence of an external magnetic field. Although the phase velocity of the magnetized quantum breathing mode is greater than that of unmagnetized quantum breathing mode, attenuation of the magnetized quantum breathing mode along radial distance seems to be slower than that of unmagnetized quantum breathing mode. Clearly, drawing the quantum breathing mode in the presence and absence of a magnetic field, we found that the magnetic field alters the distribution of dust particles and changes the radial and azimuthal velocities around the axis. Because the magnetic field rotates the dust particles and collects them, it could compensate the void structure.

Keywords: the linear quantum hydrodynamic model, the magnetized quantum breathing mode, the quantum dispersion relation of rotation mode, void structure

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Authors: Omid Kalatpour, Mohammadreza Ajdari

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This article studied the possible causes of human error-induced incidents in the petrochemical industry maintenance activities by using Human Factors Analysis and Classification System (HFACS). The purpose of the study was anticipating and identifying these causes and proposing corrective and preventive actions. Maintenance department in a petrochemical company was selected for research. A checklist of human error-induced incidents was developed based on four HFACS main levels and nineteen sub-groups. Hierarchical task analysis (HTA) technique was used to identify maintenance activities and tasks. The main causes of possible incidents were identified by checklist and recorded. Corrective and preventive actions were defined depending on priority. Analyzing the worksheets of 444 activities in four levels of HFACS showed 37.6% of the causes were at the level of unsafe actions, 27.5% at the level of unsafe supervision, 20.9% at the level of preconditions for unsafe acts and 14% of the causes were at the level of organizational effects. The HFACS sub-groups showed errors (24.36%) inadequate supervision (14.89%) and violations (13.26%) with the most frequency. According to findings of this study, increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing the human error-induced incidents in petrochemical industry maintenance.

Keywords: human error, petrochemical industry, maintenance, HFACS

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Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

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Authors: M. Nageswara Rao, V. S. N. K. Chaitanya, K. Amarendranath

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This paper presents an optimal allocation and sizing of Distributed Generation (DG) in Radial Distribution Network (RDN) for total power loss minimization and enhances the voltage profile of the system. The two main important part of this study first is to find optimal allocation and second is optimum size of DG. The locations of DGs are identified by Analytical expressions and crow search algorithm has been employed to determine the optimum size of DG. In this study, the DG has been placed on single and multiple allocations.CSA is a meta-heuristic algorithm inspired by the intelligent behavior of the crows. Crows stores their excess food in different locations and memorizes those locations to retrieve it when it is needed. They follow each other to do thievery to obtain better food source. This analysis is tested on IEEE 33 bus and IEEE 69 bus under MATLAB environment and the results are compared with existing methods.

Keywords: analytical expression, distributed generation, crow search algorithm, power loss, voltage profile

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: wheeled mobile robot, terrain, wheel slippage, odometryerror, trajectory

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Authors: Chek Kim Loi

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The study attempts to undertake an error analysis of prepositions employed in the written work of Form 4 Malay ESL (English as a Second Language) students in Malaysia. The error analysis is undertaken using Richards’s (1974) framework of intralingual and interlingual errors and Bennett’s (1975) framework in identifying prepositional concepts found in the sample. The study first identifies common prepositional errors in the written texts of 150 student participants. It then measures the relative intensities of these errors and finds out the possible causes for the occurrences of these errors. In this study, one significant finding is that among the nine concepts of prepositions examined, the participant students tended to make errors in the use of prepositions of time and place. The present study has pedagogical implications in teaching English prepositions to Malay ESL students.

Keywords: error, interlingual, intralingual, preposition

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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

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Oscar Javier Herrera, Manuel Angel Camacho

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This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: demand forecasting, empirical distribution, propagation of error, Bogota

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Authors: Nilgün Katrancı, Pınar Göv

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With the acceleration and assessment of quality and patient safety works in healthcare services in the 21st century, activities to reduce errors have gained importance. The prevention and reduction of unintended consequences related to healthcare services and errors made during the delivery of healthcare services can be achieved by understanding the causes of the errors. Communication is the basic reason most frequently seen in such cases. Nurses who communicate with patients more closely and for longer time play a more critical role in ensuring patient safety compared to other healthcare professionals. To reduce the risk of medical errors and increase the quality of care, it is important to raise the awareness of nurses about patient safety in training period. This descriptive study was conducted between February 2017 and May 2017 to assess intern students' attitudes towards and knowledge of patient safety and medical errors. The target population of the study consists of intern students at the Faculty of Nursing in Gaziantep University (N=180). The study did not apply any sample selection method, and the research group consisted of 90 female and 37 male senior students who were available and accepted to take part in the study (N=127). The study used personal information form and medical error attitude scale to collect data. The medical error attitude scale consists of 16 items and 3 sub-dimensions. The most frequently seen medical error in the clinics the interns worked at was found as ‘Failure to comply with asepsis rules’ with a rate of 67,7%. The most frequent case among reasons for not disclosing an error is ‘noticing and correcting the error before affecting the patient’ with the rate of 70,9%. The most frequently expressed implications of disclosing a serious error for the intern students participating in the study are ‘harming patient trust (78%)’ and ‘possibility of overreaction by patient (62,2%)’. According to the results of the study, the awareness of the students about the importance of medical errors and error reporting was found high (3,48 ± 0,49). Consequently, it is important to assess and positively improve the attitudes of nurses and other healthcare professionals towards medical errors for the determination of causes of medical errors and their prevention.

Keywords: healthcare service, intern student, medical error, patient safety

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

Procedia PDF Downloads 118

Authors: Marta Cordero-Gracia, Mariola Gomez, Olivier Blesbois, Marina Carrion

Abstract:

One of the difficulties in icing simulations is for extended periods of exposure, when very large ice shapes are created. As well as being large, they can have complex shapes, such as a double horn. For icing simulations, these configurations are currently computed in several steps. The icing step is stopped when the ice shapes become too large, at which point a new mesh has to be created to allow for further CFD and ice growth simulations to be performed. This can be very costly, and is a limiting factor in the simulations that can be performed. A way to avoid the costly human intervention in the re-meshing step of multistep icing computation is to use mesh deformation instead of re-meshing. The aim of the present work is to apply an interpolation method based on Radial Basis Functions (RBF) to transfer deformations from surface mesh to volume mesh. This deformation tool has been developed specifically for icing problems. It is able to deal with localized, sharp and large deformations, unlike the tools traditionally used for more smooth wing deformations. This tool will be presented along with validation on typical two-dimensional icing shapes.

Keywords: ice accretion, interpolation, mesh deformation, radial basis functions

Procedia PDF Downloads 313

Authors: Young Hee Geum

Abstract:

We propose the numerical method defined by xn+1 = xn − λ[f(xn − μh(xn))/]f'(xn) , n ∈ N, and determine the control parameter λ and μ to converge cubically. In addition, we derive the asymptotic error constant. Applying this proposed scheme to various test functions, numerical results show a good agreement with the theory analyzed in this paper and are proven using Mathematica with its high-precision computability.

Keywords: asymptotic error constant, iterative method, multiple root, root-finding

Procedia PDF Downloads 220

Authors: Papitchaya Papangkorn

Abstract:

Matching the expectations of teachers and learners is significant for successful language learning. Moreover, teachers should discover what their learners think and feel about what and how they want to learn. Therefore, this study investigates International College, Suan Sunandha Rajabhat University students’ preferences toward error corrections in order to help SSRUIC teachers match their expectations and their learners because it is important for successful language learning. This study examined the learners’ attitude and preference toward error correction through 50 first year SSRUIC students both male (25) and female (25) in Bangkok, Thailand. The data were collected from a questionnaire and interviews to investigate the necessity and frequency, timing, type of errors, method of corrective feedback, and person who gives error correction in order to answer the overall research question and sub-questions. The findings indicate five suggestions regarding the overall research question. Firstly, errors should be treated, and always be treated. Secondly, treating errors after finish speaking is the most appropriate time. Thirdly, “errors that may cause problems in an understanding of listener” and “frequent spoken errors” should be treated. Fourthly, repetition and explicit feedback were the most popular types of feedback among males, whereas metalinguistic feedback was the most favoured types amongst females. Finally, teachers were the most preferred person to deliver corrective feedback for the learners. Although the results of the study are difficult to generalize to a larger population, which are Thai EFL learners because of the small sample, the findings provide useful information that may contribute to understanding of SSRUIC learners’ preferences toward error corrections and it might reduce the gap between what teachers employ and what students expect when receiving corrective feedback. The reduction of this gap may be useful for the learning process and could enhance the efforts of both teachers and learners in a Thai context.

Keywords: attitude, corrective feedback, error, preference

Procedia PDF Downloads 357