The effect of autocorrelation on the performance of MEWMA control chart with controlled correlation

Control charts are made to identify assignable causes of difference that could exist in production processes. When traditional control charts are utilized you have the implied presumption that this observations are independently and identically distributed as time passes. It is usually believed the probability distribution which represents the actual observations includes a known functional form and it is constant as time passes. Nevertheless, in reality, observations produced through continuous in addition to discrete generation procedures in many cases are serially correlated. Auto correlation not just breaks the actual independence assumption of conventional control charts, but also can impact the efficiency associated with control charts negatively. In this article, we are going to investigate the result associated with autocorrelation around the performance of MEWMA control chart, in which autocorrelated data were utilized to create the MEWMA chart with induced autocorrelation from various levels of correlations (small, moderate as well as large) and different sample sizes. Simulations had been done to create the data set used to construct the MEWMA control chart and the outcomes implies that all of the control charts constructed had their points outside the designed control limits, that confirmed the effect of autocorrelation to the performance of the MEWMA control chart

Improved performance of MCUSUM control chart with autocorrelation

In recent years, the importance of quality has become increasingly apparent, and quality control in manufacturing has moved from detecting nonconforming products through inspection to detecting quality abnormalities in the process using statistical process control [1]. where it is used effectively, SPC plays an important role in reducing variation in manufactured items and in increasing the competitiveness of the manufacturer by improving product quality while at the same time decreasing production costs. Charts like the Shewhart X and R charts have found wide use in industry because of their ease of use for technicians and others with minimal training in statistics, since the calculations and plotting can be done by hand. An MCUSUM control chart was constructed with autocorrelated data at different levels of autocorrelation and found to be ineffective in detecting shifts as it occurs. In this article, we have proposed new techniques that can improve the performance of the MCUSUM with autocorrelation using run rule schemes. The techniques was evaluated using ARL measures of performance with 10000 iterations to simulate. The results showed that the performance of MCUSUM with autocorrelation has improved significantly with the new technique which was compared to the existing conventional MCUSUM control chart

Direct numerical method for solving a class of fourth-order partial differential equation

In this paper, we classified a class of fourth-order partial differential equations (PDEs) to be fourth-order PDE of type I, II, III and IV. The PDE of type IV is solved by using an efficient numerical method. The PDE is first transformed to a system of fourth-order ordinary differential equations (ODEs) using the method of lines, then the resulting system of fourth-order ODEs is solved using direct Runge-Kutta method (RKFD). The RKFD method is constructed purposely for solving special fourth-order ODEs. Numerical results demonstrated that the RKFD method is in good agreement with the exact solutions

Optimized fourth-order Runge-Kutta method for solving oscillatory problems

In this article, we develop a Runge-Kutta method with invalidation of phase lag, phase lag's derivatives and amplification error to solve second-order initial value problem (IVP) with oscillating solutions. The new method depends on the explicit Runge-Kutta method of algebraic order four. Numerical tests from its implementation to well-known oscillatory problems illustrate the robustness and competence of the new method as compared to the well-known Runge-Kutta methods in the scientific literature

Problem-solving skills and suicidal ideation among Malaysian college students: the mediating role of hopelessness

Objective: Recent evidence suggests that suicidal ideation has increased among Malaysian college students over the past two decades; therefore, it is essential to increase our knowledge concerning the etiology of suicidal ideation among Malaysian college students. This study was conducted to examine the relationships between problem-solving skills, hopelessness, and suicidal ideation among Malaysian college students. Methods: The participants included 500 undergraduate students from two Malaysian public universities who completed the self-report questionnaires. Results: Structural equation modeling estimated that college students with poor problem-solving confidence, external personal control of emotion, and avoiding style were more likely to report suicidal ideation. Hopelessness partially mediated the relationship between problem-solving skills and suicidal ideation. Conclusion: These findings reinforce the importance of poor problem-solving skills and hopelessness as risk factors for suicidal ideation among college students

The role of hardiness in reducing stress and suicidal ideation in a sample of undergraduates students

Suicide is a serious and growing public health problem, and it remains a serious cause of death in the world; therefore, it is essential to increase our knowledge concerning the etiology of suicide among undergraduate students. Previous studies have shown that perceived stress increases vulnerability to suicidal ideation. However, factors that may explain the association have not been studied empirically. A cross-sectional study was conducted to examine hardiness as a potential mediator between perceived stress and suicidal ideation among undergraduate students. The participants comprised 500 undergraduate students from Malaysian public universities. They completed the Personal Views Survey, Beck Scale for Suicidal Ideation, and the Perceived Stress Scale. Structural equation modeling estimated that undergraduate students with low levels of hardiness were more likely to report suicidal ideation. As expected, hardiness partially mediated between perceived stress and suicidal ideation. Our findings demonstrated that lower hardiness and greater perceived stress significantly predicted suicidal ideation among undergraduate students. These findings reinforce the importance of hardiness as a protective and predictive factor against perceived stress and suicidal ideation among undergraduate students

Fourth-order improved Runge–Kutta method for directly solving special third-order ordinary differential equations

In this paper, fourth-order improved Runge–Kutta method (IRKD) for directly solving a special third-order ordinary differential equation is constructed. The fourth-order IRKD method has a lower number of function evaluations compared with the fourth-order Runge–Kutta method. The stability polynomial of the method is given. Numerical comparisons are also performed using the existing Runge–Kutta method after reducing the problems into a system of first-order equations and solving them, and direct RKD method for solving special third-order ordinary differential equations. Numerical examples are presented to illustrate the efficiency and the accuracy of the new method in terms of number of function evaluations as well as max absolute error

A new vertical edge detection algorithm and its application

Edge detection is a very important process for many image processing applications, especially in Car License Plate Detection and Recognition Systems(CLPDRS). The need to distinguish the desired details is a very important pre-process in order to give good results in short time processing. We proposed a new and fast vertical edge detection algorithm (VEDA) which is based on the contrast between the gray scale values. Once, input gray image was binarized by using adaptive threshold, unwanted lines elimination algorithm (ULEA) was proposed and applied. After that, a VEDA was applied for experimental images. Then, implementation on the application is performed and discussed in order to confirm that VEDA is robust for highlighting license plate details easily. The results revealed accurate edge detection performance and demonstrated the great efficiency of using VEDA in order to highlight license plate details. Finally, VEDA showed that it is faster than Sobel operator by about 7-9 times

Car license plate detection method for Malaysian plates-styles by using a web camera

Recently, license plate detection has been used in many applications especially in transportation systems. Many methods have been proposed in order to detect license plates, but most of them work under restricted conditions such as fixed illumination, stationary background, and high resolution images. License plate detection plays an important role in car license plate recognition systems because it affects the accuracy and processing time of the system. This work aims to build a Car License Plate Detection (CLPD) system at a lower cost of its hardware devices and with less complexity of algorithms' design, and then compare its performance with the local CAR Plate Extraction Technology (CARPET). As Malaysian plates have special design and they differ from other international plates, this work tries to compare two likely-design methods. The images are taken using a web camera for both the systems. One of the most important contributions in this paper is that the proposed CLPD method uses Vertical Edge Detection Algorithm (VEDA) to extract the vertical edges of plates. The proposed CLPD method can work to detect the region of car license plates. The method shows the total time of processing one 352x288 image is 47.7 ms, and it meets the requirement of real time processing. Under the experiment datasets, which were taken from real scenes, 579 out of 643 images were successfully detected. Meanwhile, the average accuracy of locating car license plate was 90%. In this work, a comparison between CARPET and the proposed CLPD method for the same tested images was done in terms of detection rate and efficiency. The results indicated that the detection rate was 92% and 84% for the CLPD method and CARPET, respectively. The results also showed that the CLPD method could work using dark images to detect license plates, whereas CARPET had failed to do so

Integration for special third-order ordinary differential equations using improved Runge-Kutta direct method

In this paper, we derive an explicit four stage fifth-order Improved Runge-Kutta (IRKD) method for numerical integration of special third-order ordinary differential equation. The method proposed here is two-step in nature and require less number of stages per step compared with the existing Runge-Kutta (RK) method. The stability polynomial of the IRKD method is presented. Numerical results are given to illustrate the efficiency of the proposed method compared to the RK method and direct Runge-Kutta (RKD) method for solving special third-order ordinary differential equations