Flexible manufacturing system utilizing computer integrated control and modeling

In today\u27s fast-automated production, Flexible Manufacturing Systems (FMS) play a very important role by processing a variety of different types of workpieces simultaneously. This study provides valuable information about existing FMS workcells and brings to light a unique concept called Programmable Automation. Another integrated concept of programmable automation that is discussed is the use of two feasibility approaches towards modeling and controlling FMS operations; the most commonly used is programmable logic controllers (PLC), and the other one, which has not yet implemented in many industrial applications is Petri Net controllers (PN). This latter method is a unique powerful technique to study and analyze any production line or any facility, and it can be used in many other applications of automatic control. Programmable Automation uses a processor in conventional metal working machines to perform certain tasks through program instructions. Drilling, milling and chamfering machines are good examples for such automation. Keeping the above issues in concem; this research focuses on other core components that are used in the FMS workcell at New Jersey Institute of Technology, such as; industrial robots, material handling system and finally computer vision

Assessment of Job Satisfaction among Faculty Members and its Relationship With Some Variables in Najran University

It is vital that colleges and universities monitor the satisfaction levels of their employees to secure high levels of their performance. The current study aimed to identify the impact of some variables (gender, Teaching experience and college type)on assessing the level of job satisfaction among faculty of Najran University. A survey was conducted in this study by a 23-item questionnaire, distributed to (262) male and female faculty members from various colleges. The questionnaire items distributed to four domains: Academic environment, salaries and financial support, psychological and social aspects, and interpersonal communication. The results showed a moderate degree of job satisfaction in general, and there are statistically significant differences due to (gender, teaching experience and college type), where the differences in favor of males, scientific colleges and more experienced. Keywords: job satisfaction, assessment, faculty and Najran Universit

Credit Risk, Macroeconomic and Bank Specific Factors in Jordanian Banks

High volume of risks facing banks is one of the most important reasons behind their failure. The exposure of banks to risks measured by risk index could indicate the extent of the vulnerability of banks to adverse performance. This thesis applies risk index to measure risk exposure of 23 Jordanian banks during 1995 to 2008. Findings reveal that the average risk index of banks is 17.5 units in comparison to the mean industry index of 17.9 units. The lower value for risk index for the banks in the sample in comparison to the industry mean reflects the higher risk borne by some of the banks in the sample. Further investigation provides evidence that a bank with a higher risk index level has strong capital and profit relative to the volatility of their returns. Among the banks, Arab Jordan Investment Bank has the highest index of 33.3 units, while Jordan Investment and Finance Bank has the lowest index of 6.8 units. For industry risk index, the highest value for the risk index is 35 units (in 2006), while the lowest of 11 units in 1997. The low risk index showed high risks faced by the Jordanian banks in 1997. This is due to low economic performance where GDP decline from 6.2 percent in 1995 to 2.1 percent and 3.3 percent in 1996 and 1997 respectively. Most banks achieved low net income, which affect negatively their profitability. In addition to measure risk index, this thesis investigates the relationship between risk index and banks size. Results show that there exist significant differences between the mean of risk index between large, medium and small banks. Large banks have a significant mean difference among group of banks. Moreover, a positive and significant relationship was found between risk index and banks' size, which suggest that the larger the banks, the safer they are. This thesis also measures market risk of banks during the test period using single index market model and Dimson's procedure with 2 lag and 1 lead to correct non-synchronous trading effect. The results show that the average market risk (beta) measure of Jordanian listed banks over 1995-2008 is 0.461, which indicates a very low market risk in terms of price volatility. Among the banks, Arab Bank has the highest average beta of 0.766, and Ahli Bank has the lowest market risk of 0.327. An investigation of the trend of average market risk during a study period reveal that the changes in market risk are mainly due to a fluctuation of financial market and movements of the prevailing interest rate. Finally, this thesis investigates the determining variables of credit risk among the sample banks. According to the Capital Assets Pricing theory, risks are attributable by external factors and internal factors. Hence, twelve variables comprising five macroeconomic variables (aggregate economic activity, inflation, money supply, interest rate and market risk), and seven bank specific variables (lag non performing loans, provision of loan losses, loan growth, equity capital ratio, loan concentration in risky sectors, net interest margin and size) are applied as independent variables. The dependent variable is credit risk, which is measured by non performing loans to total loans ratio. Four theories which are financial intermediation theory, agency theory, diversification theory and capital assets theory formed the theoretical framework in this study. OLS regression model was used to investigate the determinants of credit risk in the Jordanian banks. The results show that all the macroeconomic variables together explain 51.9 percent of the variation of credit risk. From the five macroeconomic variables, three were found statistically significant. They are GDP, inflation and market interest rate. Our study shows that bank specific variables were found to affect credit risk more than the external variables. All bank specific variables explain 73 percent variation of credit risk. This indicates a strong association between bank specific variables and banks credit risk exposure. Five variables which are non performing loan, loan growth, loan concentration in risky sectors and banks size were found as significant determinants of credit risk at the Jordanian banks. On a pool basis, all macroeconomic variables and bank specific variables together explain 72 percent of the banks' credit risk. For the whole model, net interest margin was found significant and negatively related to credit risk. In conclusion, this thesis assesses the risk exposure and for the first time, empirically determines the variables affecting credit risk of the Jordanian banks. As credit risk is the main risk that could lead to bank failure, the results imply that the management of the Jordanian banks should pay great attention to the significant factors, in particular their non performing loans and loan growth. The positive and significant relationship between banks' risk index and their size supports the Basel Accord standards, where the greater the bank risks, the higher should be the size of their capital base in order to ensure that the risks adequately be covered

A new structure of an integral operator associated with trigonometric Dunkl settings

In this paper, we discuss a generalization to the Cherednik-Opdam integral operator to an abstract space of Boehmians. We introduce sets of Boehmians and establish delta sequences and certain class of convolution products. Then we prove that the extended Cherednik-Opdam integral operator is linear, bijective and continuous with respect to the convergence of the generalized spaces of Boehmians. Moreover, we derive embeddings and discuss properties of the generalized theory. Moreover, we obtain an inversion formula and provide several results

Iterative Reproducing Kernel Method for Solving Second-Order Integrodifferential Equations of Fredholm Type

We present an efficient iterative method for solving a class of nonlinear second-order Fredholm integrodifferential equations associated with different boundary conditions. A simple algorithm is given to obtain the approximate solutions for this type of equations based on the reproducing kernel space method. The solution obtained by the method takes form of a convergent series with easily computable components. Furthermore, the error of the approximate solution is monotone decreasing with the increasing of nodal points. The reliability and efficiency of the proposed algorithm are demonstrated by some numerical experiments

A transfer learning with deep neural network approach for diabetic retinopathy classification

Diabetic retinopathy is an eye disease caused by high blood sugar and pressure which damages the blood vessels in the eye. Diabetic retinopathy is the root cause of more than 1% of the blindness worldwide. Early detection of this disease is crucial as it prevents it from progressing to a more severe level. However, the current machine learning-based approaches for detecting the severity level of diabetic retinopathy are either, i) rely on manually extracting features which makes an approach unpractical, or ii) trained on small dataset thus cannot be generalized. In this study, we propose a transfer learning-based approach for detecting the severity level of the diabetic retinopathy with high accuracy. Our model is a deep learning model based on global average pooling (GAP) technique with various pre-trained convolutional neural net- work (CNN) models. The experimental results of our approach, in which our best model achieved 82.4% quadratic weighted kappa (QWK), corroborate the ability of our model to detect the severity level of diabetic retinopathy efficiently

Using deep learning models for learning semantic text similarity of Arabic questions

Question-answering platforms serve millions of users seeking knowledge and solutions for their daily life problems. However, many knowledge seekers are facing the challenge to find the right answer among similar answered questions and writer’s responding to asked questions feel like they need to repeat answers many times for similar questions. This research aims at tackling the problem of learning the semantic text similarity among different asked questions by using deep learning. Three models are implemented to address the aforementioned problem: i) a supervised-machine learning model using XGBoost trained with pre-defined features, ii) an adapted Siamese-based deep learning recurrent architecture trained with pre-defined features, and iii) a Pre-trained deep bidirectional transformer based on BERT model. Proposed models were evaluated using a reference Arabic dataset from the mawdoo3.com company. Evaluation results show that the BERT-based model outperforms the other two models with an F1=92.99%, whereas the Siamese-based model comes in the second place with F1=89.048%, and finally, the XGBoost as a baseline model achieved the lowest result of F1=86.086%

A Novel Representation of the Exact Solution for Differential Algebraic Equations System Using Residual Power-Series Method

We implement a relatively new analytic iterative technique to get approximate solutions of differential algebraic equations system based on generalized Taylor series formula. The solution methodology is based on generating the residual power series expansion solution in the form of a rapidly convergent series with easily computable components. The residual power series method (RPSM) can be used as an alternative scheme to obtain analytical approximate solution of different types of differential algebraic equations system applied in mathematics. Simulations and test problems were analyzed to demonstrate the procedure and confirm the performance of the proposed method, as well as to show its potentiality, generality, viability, and simplicity. The results reveal that the proposed method is very effective, straightforward, and convenient for solving different forms of such systems