MATLAB R2013a Research Articles

Design and Implement an Application to Measure the Readiness of Teachers to Adopt E-learning in Mosul Schools After Pandemic COVID-19

Nowadays, due to the rapid increment of the pandemic COVID-19 which affects the teaching environment, a need appeared to use a new alternative education style, which helps to decrement the injuries and the continuation of the education. This study designs an application to measure the teachers’ readiness to use e-learning. A questionnaire was designed to collect as much information as possible to measure the teachers' readiness to adopt e-learning in Iraqi schools after pandemic COVID-19 by analyzing the factors that affect the education process. The questionnaire consists of thirty-three questions in the Arabic language and includes three sections (background information, attitude toward e-learning, and computer skills). The collected responses are taken from Mosul’s primary and secondary schools’ teachers and the sample size is (261). A test of reliability was carried out on the study instrument, and the value of Cronbach’s alpha was 0.913. The MATLAB R2014a was used to build an application in order to do the analyzing process and determine the readiness of e-learning.

Wave-based method for longitudinal vibrational analysis of irregular single-walled carbon nanotube with elastic-support boundary conditions

The longitudinal vibrationnal analysis of an irregular single-walled carbon nanotube (ISWCNT) with elastic boundary restraints along its ends is invistigated in this study. The Flügge’s principle is employed to model the ISWCNT and the wave propagation approach is utilized to evaluate the natural frequncy of longitudinal vibration of ISWCNT. The boundary conditions and governing equations are formulated based on Flügge’s model. An exact solution is presented in the axial direction and the MATLAB R2013a Software is hired to present a numerical solution for the longitudinal vibration. A novel equation of motion and frequancy equation are derived for vibrational analysis of ISWCNT under the elastic-support boundary conditions in the longitudinal direction and the impacts of surface irregularity parameter are investigated to find a better profile for irregularity varation to maximize the vibration stability of ISWCNTs. It is concluded that, the irregular single-walled carbon nanotubes or those whose natural frequencies decrease from the large irregularity parameter to the small irregularity parameter of SWCNTs are not optimum designs to build appropriate nanodevices for various applications. In addition, it is observed that to improve the vibration stability of ISWCNTs, it is better to decrease surface irregularity from the large to the small irregularity parameter. Results of this work can be utilized to provide optimum designs for nanodevice in which ISWCNT is common nanocomposite structural element.

Wind Energy Resource Prediction and Optimal Storage Sizing to Guarantee Dispatchability: A Case Study in the Kenyan Power Grid

Kenya is experiencing a fast increase in grid-connected intermittent renewable energy sources (RESs) to meet its increased power demand, and at the same time be able to fulfill its Paris Agreement obligations of abating greenhouse gas emissions. For instance, Kenya has 102 MW of grid-tied solar power and 410 MW of grid-tied wind power. However, these sources are very intermittent with low predictability. Thus, after their installation and integration into the grid, they impose a new challenge for the secure, reliable, and economic operation of the system. To mitigate these and to ensure proper planning of the system operations, accurate and faster prediction of the generation output of the wind energy resources and optimal design and sizing of storage for the large-scale wind energy integration into the grid are of paramount importance. Artificial intelligence (AI) and metaheuristic techniques have proven to be efficient and robust in offering solutions to complex nonlinear prediction and optimization problems. Therefore, this study aims to utilize backpropagation neural network (BPNN) algorithm to conduct hourly prediction of the generation output of Lake Turkana Wind Power Plant (LTWPP), a 310 MW plant connected to the Kenyan power grid, and optimally size its battery energy storage system (BESS) using genetic algorithm (GA) to guarantee its dispatchability. The historical weather data, namely wind speed, ambient temperature, relative humidity, wind direction, and generation output from LTWPP, are employed in the training, testing, and validation of the neural network. LTWPP and BESS are modelled in MATLAB R2016a software. Thereafter, the developed BPNN and GA algorithms are applied to the modelled systems to predict the wind output and optimize the storage system, respectively. BESS optimization with neural prediction reduces the BESS capacity and investment costs by 59.82%, while the overall dispatchability of LTWPP is increased from 73.36% to 90.14%, hence enabling the farm to meet its allowable loss of power supply probability (LPSP) index of 0.1 while guaranteeing its dispatchability.

Refractive and biometrical characteristics of children with retinopathy of prematurity who received laser photocoagulation or intravitreal ranibizumab injection.

To investigate the refractive and biometrical developments of children with retinopathy of prematurity (ROP) who received laser photocoagulation (LP) or intravitreal ranibizumab injection as treatment. This case-control study involved cases with Zone II Stage 3 ROP. Fourteen children (28 eyes) who received single LP were included in the laser group, and 14 children (27 eyes) who received single intravitreal ranibizumab injection were included in the injection group. The mean age at operation was 37.00±1.72 and 36.36±1.66 weeks for the laser and injection groups, respectively (P=0.161), and refraction measurements and biometry were performed at the mean age of 5.00±1.63 and 5.00±0.94 years for the laser and injection groups, respectively (P=1.000). Spherical equivalent (SE) after mydriatic refraction and best corrected visual acuity (BCVA) were measured by refraction test. Central corneal thickness (CCT), anterior corneal surface curvature and curvature radius, anterior chamber depth (ACD), lens thickness (LT) and axial length (AL) were measured by biometry using the IOL Master700 biometric instrument (Carl Zeiss Meditec AG). The biometrical images were reanalysed using a self-developed program in MATLAB (R2016a, MathWorks, Inc.) to obtain additional eye parameters, including the curvatures of the posterior cornea and the anterior and posterior surfaces of the lens. SPSS (V.23.0) was used for statistical analysis. Independent sample t test was used to compare the eyeball biological and refractive state measures of the two groups, and Pearson correlation coefficient was used to evaluate the correlation between SE and the biological parameters. 1. (1) Cornea-related parameters: CCT (0.54±0.04mm vs 0.55±0.02mm, P>0.05), anterior corneal surface curvature radius (7.56±0.26 mm vs 7.67±0.43mm, P>0.05) and posterior corneal surface curvature radius (6.82±0.27mm vs 6.79±0.42mm, P>0.05). (2) ACD (3.21 ± 0.25mm vs 3.22 ± 0.19mm, P>0.05). (3) Lens-related parameters: anterior lens surface curvature radius (10.04±0.89mm vs 9.82±1.08mm, P>0.05), posterior lens surface curvature radius (5.49±0.55mm vs 5.92±0.73mm, P<0.05) and LT (3.80±0.14mm vs 3.59±0.16mm, P<0.05). (4) AL (21.82±1.07 vs 22.68±1.61, P<0.05). (5) Parameters related to refractive state: SE (-2.43±3.56 vs -0.53±3.12, P<0.05) and BCVA (log MAR, 0.17±0.14 vs 0.21±0.18, P>0.05). 2. (1) The SE of children in the laser group was positively correlated with LT (r=0.438, P<0.05), negatively correlated with ACD (r=-0.437, P<0.05) and had no significant correlation with other eyeball biological indicators (P>0.05). (2) The SE of children in the injection group was negatively correlated with AL (r=-0.537, P<0.05), positively correlated with CCT (r=0.455, P<0.05) and had no significant correlation with other eyeball biological indicators (P>0.05). LP and intravitreal ranibizumab injection as ROP treatments produce myopic refraction with increased degree of myopia in children who received LP than in children who received ranibizumab injection. The increased myopia after LP is due to the increases in LT and posterior lens curvature and a shallow ACD.

Koordinasi Proteksi Relai Arus Lebih pada Sistem Distribusi Radial Menggunakan Jaringan Syaraf Tiruan Perambatan Balik

&lt;p&gt;&lt;em&gt;To reduce damage to electrical power equipment, protective equipment is needed that is designed as well as possible, so that the protection relay can isolate faults in parts of the distribution network as fast as possible. This backup protection need appropriate relay coordination, so that could protect, if it happens of a primary protection failure. To provide the best service to customers, it is necessary to coordinate the protection relay in the electric power system. To provide protection, the protection relay in the electric power system must be properly coordinated. In this study, we will make a simulation to calculate the TDS and Ipickup values of the overcurrent relay using a artificial neural network backpropagation with software Matlab R2016a. The results of this study can determine the value of TDS (Time Dial Setting) and Ipickup (Current pickup) by overcome the main problem of overcurrent relay protection coordination at the Ammurea II Factory PT. Petrokimia Gresik using a method artificial neural network backpropagation. And, also obtained the results of the minimum value of MSE (Mean Square Error) with the process using the method artificial neural network backpropagation.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;br /&gt;&lt;/em&gt;&lt;/p&gt;

Significant Differences in the Value of the Void Fraction in Various Types of Low-Viscosity Two-Phase Flow Patterns in Capillary Tubes with a Particular Slope

A two-phase flow is the simplest form of multi-phase flow. Two-phase flow has basic parameters, including flow behavior, flow pattern, void fraction, pressure gradient, or pressure drop. The development and application of fluid flow in small channels (mini and micro) are in the Micro Electromechanical System (MEMS). In general, the application of two-phase flow can be found in various applications in the industrial world, such as boilers, cores, and steam generators in nuclear reactors, petroleum transportation, electronic cooling, and different other types of chemical reactors. One of the most common challenges is void fractions and flow patterns in horizontal and vertical pipelines. The purpose of this study was to find out the significant difference in the characteristic value of fundamental parameters, primarily void fractions and flow patterns that occur in capillary pipes with a slope of 15o to horizontal. The fraction value and shape of this flow pattern are essential because it determines the pressure drop value, which means determining the level of danger that can occur if the pressure drop value reaches the extreme value. The fluid used a mixture of air-water and glycerin with 0, 10, 20, and 30% concentrations. To determine the void fraction is used digital image processing method with MATLAB R2014a application. A 1200 fps high-speed camera and 640 x 480-pixel resolution are used for video shooting. The experiment was conducted at superficial gas (JG) velocities of 0.025 - 66.3 m/s and superficial fluid velocities (JG) intervals of 0.033 – 4.935 m/s. The experiment results showed a significant difference between the void fraction value for the bubbly flow pattern and the churn flow pattern, which has not been widely discussed in previous studies. The analysis concluded that the higher the velocity of superficial gases, the void fraction value increases. This increase in the void fraction is why there is a significant change in flow patterns from bubble flow patterns to churn. In addition, it was also found that the increased viscosity of the fluid significantly affected changes in flow patterns, incredibly bubbly and plug, but its velocity decreased. It is also the result that the higher homogeneous void fraction (β) value affects the increase in the length of bubbly flow patterns and plugs.

Lock-in in the vortex-induced vibrations of a long tensioned riser in internal fluid flow and external uniform and shear flows: A prediction based on models

In this study, the occurrence of lock-in, indicating local synchronization between the vortex shedding and cross-flow (CF) structural vibration frequencies, is investigated for a long tensioned and simply-supported riser conveying internal fluid flow that is free to move in the in-line (IL) and CF directions and immersed in uniform flow (UF) and linear shear flow (SF). Our established models are used to perform a numerical simulation, describing the unsteady hydrodynamic forces associated with wake dynamics using two van der Pol wake oscillators in the IL and CF directions coupled with the riser. The riser is discretized into a string of spatial slender beam elements, and the wake oscillators are distributed on the element nodes. MATLAB (R2014a) is used to establish a computational program verified using existing experimental data. The lock-in frequency and location are captured by comparing the wake model's CF oscillation frequency with the riser's CF vibration frequency at every node of the finite element system when both coincide at the frequency and location. The influences of the oncoming flow velocity, fluid's conveying velocity in the riser and the tension on the lock-in frequency, as well as the lock-in distribution along the riser axis, are discussed. In the UF, the high oncoming flow velocity (0.42 m s−1) promotes the occurrence of the lock-in at a higher frequency. When the oncoming flow velocity is high in the UF and linear SF, the internal fluid conveying velocity and tension have little influence on the lock-in condition. The present results do not always agree with the classic outcome in linear SF that the lock-in occurs in the region with a high oncoming flow velocity over at least 30% of the riser's length.

Industry 4.0 Roadmapping: A Fuzzy Linguistic Approach

Background: The industry 4.0 transition is becoming crucial for organizations. The lit-erature reviewed showed that whilst there are many studies on industry 4.0 assessment that help organizations to evaluate their current state, limited studies exist for road-mapping activities. Objective: The main aim of this study is to construct a model that leads organizations to their fourth industrial revolution transition. Companies, especially small and medium-sized ones (SMEs) need clear, agile and efficient road maps because of their limited resources. Lack of a procedure that guides organizations in the right way is the motivation of this study. Method: A linguistic fuzzy inference system is used in this study. Concepts are determined and relations between concepts with if-then rules have been constructed according to the expert opin-ion. MATLAB R2015a is used for the inference system. Results: An exemplary case is considered and the results show that the inference system can pro-vide company-specific roadmaps. To which extend an industry 4.0 concept should be taken into account for a company can be seen with the proposed method. Conclusion: The proposed method showed that specific and agile roadmaps could be obtained. Be-cause of the dependency of expert opinion for the fuzzy rule base, different methods for obtaining rules and relations may be a future research direction.

New artificial neural network design for Chua chaotic system prediction using FPGA hardware co-simulation

&lt;p&gt;This study aims to design a new architecture of the artificial neural networks (ANNs) using the Xilinx system generator (XSG) and its hardware co-simulation equivalent model using field programmable gate array (FPGA) to predict the behavior of Chua’s chaotic system and use it in hiding information. The work proposed consists of two main sections. In the first section, MATLAB R2016a was used to build a 3×4×3 feed forward neural network (FFNN). The training results demonstrate that FFNN training in the Bayesian regulation algorithm is sufficiently accurate to directly implement. The second section demonstrates the hardware implementation of the network with the XSG on the Xilinx artix7 xc7a100t-1csg324 chip. Finally, the message was first encrypted using a dynamic Chua system and then decrypted using ANN’s chaotic dynamics. ANN models were developed to implement hardware in the FPGA system using the IEEE 754 Single precision floating-point format. The ANN design method illustrated can be extended to other chaotic systems in general.&lt;/p&gt;

Markov Chain theoretic approach to modelling industrial safety: some results from Nigeria oil and gas industry

the oil and gas industry. This study seeks to unravel the hidden details enwrapped in the safety data which enable the development of a model that would be effective in predicting future occurrence of industrial accidents. The purpose of this study is to spotlight the epidemiological impact of industrial accidents which claim lives, maim personnel and lower productivity through loss of man-hours. The major strategy adopted consists of the examination of a 10-year unified industrial accident recorded from 2007 to 2016 in the oil and gas sector of the Niger Delta of Nigeria. The Markov Chain model was applied to determine how workers habituate among different positions in the company before getting entrapped in any of the absorbing states. The industrial accident records are examined for embedded Markov properties, namely: stochastic regularity, absorbing behavior and the long-run distribution amongst the various states. The statistical computations were carried out with the aid of Matlab (R2017a) software. The historical Health Safety and Environment (HSE) statistical data were found to have an absorbing chain property. Thirteen (13) transition states were defined and named as; fatality, medical treatment, first aid cases, Lost time injury frequency, restricted work cases, first aid case, near miss, lost time injury, environmental incident, fire incident, unsafe acts, unsafe condition and number of attendance of clinic. The result from the study also revealed that staff makes between 17-18 habituations before being trapped in an absorbing state. Remarkably, 99% of workers in the organization had severe medical treatment cases (MTCs) as a result of work-related occupational illness and injury. The implication of the study is that the safety policy outlook of this company should be reorganized to reduce its lost workdays due to minor injury and illness.

Detection of Escherichia Coli Bacteria by Using Image Processing Techniques

Recently, image processing has proven itself as a fast and reliable technique in research in medicine and biology. Bacterial colony separation is an important and time-consuming process in studies in the field of microbiology. Bacteria counting is usually carried out by the naked eye or even by Coulter counter machines, which are based on the rather expensive electric field measurement method. In this study, image-based enumeration of Escherichia Coli over the colony morphology in the petri dish was investigated. In the experimental study, 4 different bacteria from the Enterobacteriaceae family were planted on petri dishes containing Eosin-methylene blue agar (Merck, Darmstadt, Germany). Escherichia Coli colony characteristics were determined by digitizing planted bacterial petri images. For the study, counting was done with the interface developed in MATLAB R2013a. After the classification criteria were determined, the method was tested on new petri dishes and successful results were obtained.

A new scheme of global feature management improved the performance and stability of radiomics model: a study based on CT images of acute brainstem infarction.

The performance and stability of radiomics model caused by dimension reduction remain being confronted with major challenges. In this study, we aimed to propose a new scheme of global feature management independent of dimension reduction to improve it. The non-contrast computed tomography (NCCT) images of acute brainstem infarction (ABI) from two medical centers were used as test and validation sets. A new scheme was constructed based on global feature management, and the traditional scheme dependent on dimension reduction was used as control. The radiomic features of NCCT images were extracted in Matlab R2013a. The performance of prediction model was evaluated by the generalized linear model (GLM) and multivariate logistic regression. And, the stability of radiomics model was evaluated with the difference of area under curve (AUC) between the test and validation sets. Compared with the traditional scheme, the new scheme presented a similar detection performance (AUC: 0.875 vs. 0.883), yet a better performance in predicting prognosis (AUC: 0.864, OR = 0.917, p = 0.021 vs. AUC:0.806, OR = 0.972, p = 0.007). All these results were well verified in an independent validation set. Moreover, the new scheme showed stronger stability in both the detection model (ΔAUC: 0.013 vs. 0.039) and prediction model (ΔAUC = 0.004 vs. 0.044). Although there might be several limitations, this study proved that the scheme of global feature management independent of dimension reduction could be a powerful supplement to the radiomics methodology. • The new scheme (Swavelet) presented similar detection performances for ABI with the traditional scheme. • A better predictive performance for END was found in the new scheme (Swavelet) compared with the traditional scheme. • Stronger model stability was found in both the detection and prediction models based on the new scheme.

Application of artificial neural network with the back-propagation algorithm for estimating the amount of polycyclic aromatic hydrocarbons in Tehran Oil Refinery, Iran

Oil pollution has been one of the most common environmental damages in recent decades, which has been abundant in oil-producing countries such as Iran. This study aimed at using the artificial neural network (ANN) to predict the amount of petroleum pollutants including polycyclic aromatic hydrocarbons (PAHs) in the groundwater of the Tehran Oil Refinery by a set of input features, which modeled in MATLAB R2015a. Accordingly, 13 input features were used for developing an ANN model as inputs, including pH values, electrical conductivity, total dissolved solids, and total suspended solids (TDS and TSS), distance from the source of contamination (Distance), the amount of phenol, oil and grease, and the amount of ions such as potassium, sodium, chlorine, sulfate, magnesium, and calcium. The testing and training data for learning the ANN model were produced by applying 45 data obtained from the analyzing of sample wells around the Tehran refinery in the laboratory. Due to the low number of data, back-propagation networks were employed for modeling. The regression values for training, validation, and test data were equal to 0.997, 0.991, and 0.917, respectively. Based on the results, the best validation performance was detected in epoch 13. The mean square errors were 0.00348, indicating the high accuracy of the ANN method in the prediction and estimation of PAHs in the mentioned site, and thus this model can be used on sites with similar conditions.

The prediction model of regression for the CO removal from exhaust using plasma- catalyst process

Background. The present study considers the main physicochemical parameters included in the optimum removal efficiency of carbon monoxide (CO) using the plasma-driven catalysis reactor. Material and Methods. A nonthermal plasma (NTP) –catalyst process was applied to investigate the removal efficiency of CO. The interaction of proposed factors such as; temperature, space-time, propane concentration, applied voltage, and the current was studied to estimate the optimum conditions of CO removal efficiency. Data analysis of experiments was done using General Linear Model (GLM) analysis in SPSS (version 22.0.) and fit linear regression model in MATLAB R2013a software. Results and Discussion. The results showed the interaction of temperature and space-time play a key role in CO removal (P-value <0.05). This interaction was found significantly positive with a decrease in space-time. The effect of applied voltage and current (i.e., two main parameters of power consumption) was found significant in the interaction model of C3H8/CO ratio with temperature, as well as space-time. Also, the presented regression model of results confirms the meaningful effect of interactions. Reduction of space-time is known as an energy consumption parameter controlled by reactor gap discharge, gas composition, and inner electrode material. The effect of propane presence as a reducer agent in the gas composition was found significant in the interaction model of space-time and temperature. Conclusion. Considering physicochemical parameters in designing NTP- catalyst reactors can influence energy efficiency significantly.

Design optimization of rural building in dry-hot and dry-cold area using a back propagation (BP) neural network

This study describes the numerical analyses of the indoor air temperature of the earth building located in dry-hot and dry-cold area in order to evaluate the effects of the passive design parameters on the indoor environment and then determine the optimal values of the design parameters. Firstly, a short-term monitoring was performed in an existing earth building, aiming to validate the numerical building model developed by using an advanced simulation software EnergyPlus. Then a series of regional studies on the effect of building parameters on indoor environment of the earth building were investigated and the simulated results indicated that four design parameters, i.e. building orientation, window to wall area ratio, projection factor of window shading and external wall thickness, exhibit the distinctly impacts on the indoor thermal environment in winter and summer. Next, a back propagation (BP) neural network model with ten neurons in the hidden layer was established using Matlab R2016a to predict the indoor environment, and the degree discomfort hours (DDH) in winter and summer were calculated as the output data. Finally, the itemized intensive scanning technique was used to successively select the values of the passive parameters in their range and the predicted results indicated that the optimal passive parameters are 6°east of south, 18.20 %, 0.66 and 643 mm, respectively.

Study of the Biological Developmental Characteristics of the Eye in Children After Laser Surgery for the Treatment of Retinopathy of Prematurity.

Study of the Biological Developmental Characteristics of the Eye in Children After Laser Surgery for the Treatment of Retinopathy of Prematurity.

Optimum design of a composite floor system considering environmental and economic impacts

Abstract The composite floor system, composed of steel deck and concrete slab, generates more efficient and economical structures. On the other hand, the design of this type of structure has a high complexity level due to the consideration of several variables. In this respect, the objective of this paper is to present the formulation of the optimization problem for a composite floor system (steel and concrete) considering such environmental as economic impacts. To formulate the optimization problem, the reduction of environmental impact was adopted as an objective function - assuming the CO2 emission and the finance cost as parameters. The restrictions were taken by the limiting states imposed in standard NBR 8800:2008. The computer program was developed via Matlab R2016a and the optimization process was carried out using the Genetic Algorithm toolbox existing in this platform. Two application examples of the formulation at hand are presented: the first from the literature and the second from an existing building - in both situations the influences of different concrete compressive characteristic strengths were analyzed. The results of the optimization problem show a reduction in geometry and, consequently, in its weight. The solution found by the program reduces by up to 17.70% of CO2 emissions and 17.47% of the finance cost. When was applying different concrete compressive strengths, the optimal solution for environmental impact did not get the lowest cost. In general, the steel deck formwork obtained the highest percentage of environmental impact, while the beams and girders, with the same shape configuration, had the highest finance cost. Therefore, it is shown that the optimal design solution to CO2 emissions is not always the better solution for the finance cost.

Definisanje rizika na putnim deonicama pri transportu opasnog tereta u vojsci Srbije primenom modela linearnog matematičkog programiranja

Introduction/purpose: The paper presents a model for the selection of a route for the transport of dangerous goods using DEA (Data Envelopment Analysis) models and fuzzy logic systems. The presented model is used to define the risk on road sections during the transport of dangerous goods as well as to select the optimal route for the realization of the transport task. Methods: The model consists of two phases. The first phase includes the application of DEA models in which formed input and output models are connected in the output DEA final form which shows routes with a satisfactory level of traffic safety and at the same time eliminates routes with low traffic safety. The second phase involves the application of fuzzy logic systems, and as a way out of the fuzzy system, preference is given to one route. Route evaluation is based on six criteria, namely: route length, number of access points, AADT (annual average daily traffic), the number of traffic accidents with fatalities, the number of traffic accidents with the injured and the number of traffic accidents with material damage. When the values of the input criteria are entered, a calculation and evaluation is performed, and, as an exit from the fuzzy system, preference is given to one of the entered routes (the route with the lowest level of risk). The criteria used were defined on the basis of expert assessments. Results: A user program that represents decision support in traffic service. Conclusion: The user platform was created for the Matlab R2015a software package with the ability to be adapted to specific problems.

Design of an OCR System and its Hardware Implementation

Abstract: In this paper, we present a scheme to develop to complete OCR system for printed text English Alphabet of Uppercase of different font and of different sizes so that we can use this system in Banking, Corporate, Legal industry and so on. OCR system consists of different modules like preprocessing, segmentation, feature extraction and recognition. In preprocessing step it is expected to include image gray level conversion, binary conversion etc. After finding out the feature of the segmented characters artificial neural network and can be used for Character Recognition purpose. Efforts have been made to improve the performance of character recognition using artificial neural network techniques. The proposed OCR system is capable of accepting printed document images from a file and implemented using MATLAB R2014a version. Key words: OCR, Printed text, Barcode recognition

Lock-in prediction for vortex-induced vibrations of a long hanged and weighted riser in internal fluid flow and external currents

The occurrence of lock-in, a local synchronization between the vortex shedding and cross-flow (CF) structural vibration frequencies, is investigated for a long flexible riser, of which the top is hanged and bottom is weighted and moveable in both the in-line (IL) and CF directions, conveying internal fluid flow (IF) and immersed in uniform, and linear shear currents (flows). Our established models are used to conduct a numerical simulation, in which unsteady hydrodynamic forces associated with wake dynamics are described using two van der Pol wake oscillators in both the IL and CF directions that are coupled with the riser. The riser is discretized into a string of spatial slender beam elements, and the wake oscillators are distributed on every immersed element nodes. MATLAB (R2014a) is used to establish a computational program, which is verified using existing experimental data. The lock-in frequency and location are captured by comparing the CF oscillation frequency of the wake model with the CF vibration frequency of the riser at every node of the finite element system when both coincide with each other at the frequency as well as location. The influences of the oncoming flow velocity (OFV), IF velocity (IFV) and bottom hanging weight (BHW) on the lock-in frequency, as well as the lock-in distribution along the riser axis are discussed. In UF, a high IFV (4.5 m/s) makes lock-in occurrence in riser’s “whole oncoming velocity region” in a single-frequency mode but a zero or low IFV (1.5 m/s) makes it null. In linear shear flow, a zero or low IFV (1.5 m/s) makes the lock-in occurrence in riser’s “low and middle oncoming velocity region” in a single-frequency mode and a high IFV (4.5 m/s) makes it in the “whole oncoming velocity region” in the multi-frequency modes, the lock-in frequency mode (but not the lock-in amount) is regardless of OFV and BHW in the context of this paper.