Qeethara Al-Shayea

Al-Zaytoonah University of Jordan · Department of Management Information Systems

The forecasting of the stock exchange asking price has been affected by a number of monetary and nonmanetary indexes that might be used as a warning rule for investors. Expecting the future trend of the stock market is a critical issue in investment sector. In this work, the forecasting of futurity open and close asking price of Dow Jones Industria...

An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. Condition indicators are derived from sound signals, and used to arrive at a decision about the performance state of the machine. Sound signals are recorded by microphones and processed using time-frequency domain analysis. In this study, number of stati...

Biometric face recognition including digital processing and analyzing a subject's facial structure. This system has a certain number of points and measures, including the distances between the main features such as eyes, nose and mouth, angles of features such as the jaw and forehead with the lengths of the different parts of the face. With this in...

The prediction of a stock market price has been influenced by a set of the highly nonlinear financial and non-financial indicators may serve as a warning system for investors. In this research, the predicting of the future close price of Dow Jones Index Stocks was conducted using artificial neural networks. Feed forward neural network was used to p...

Nowadays the companies are increasingly facing crisis while smart phone which combine the features of a phone with a general-purpose computer is spread increasingly. This paper presents the smart phone applications that are used to manage the crisis. In this paper we argue that these devices are a good platform for use in urgent crisis management....

Many research in artificial intelligence has been proposed over years with successful and promising results in many areas and problem domains. Models of artificial intelligence systems are presented in this paper. Expert Systems, genetic algorithms, artificial neural network systems, fuzzy systems and hybrid artificial intelligent systems represent...

The images can be visualized in three dimensional (3D) using standard techniques, these 3D techniques are used to enhance the view of images. Converting two dimensional (2D) images into 3D images is an important part of image application. An efficient approach of 3D image reconstruction is implemented to perform a certain process that applied to X-...

Speaker identification systems are an important part of the biometric techniques. Many speaker identification systems were designed and implemented during the last few years and these systems depend on different techniques. This paper presented a simple speaker identification approach based on fusion via samples and statistical approach to generate...

In this study, a modification of the Hopfield and Tank network solving the traveling salesman problem (TSP) is proposed. The proposed neural network has the same Hopfield's network configuration but without restriction to parameters. The challenge of the study is to go beyond Hopfield and Kohonen neural network model which in spite of a great theor...

There are several windows used to truncate the impulse response in order to fix filter size. Kaiser and Tukey windows are the most important types; from which we can generate other types of windows depending on the variation of ripple parameter. The proposed new window approach is called MSK 2 that was implemented to compare its parameters with the...

In cloud computing data is available at anytime and anywhere with the spread increasingly of broadband network. The paper proposes a telemedicine model to be implemented in Jordan. This model uses MATLAB server services to make decision about the patient case. At the same time this paper focuses on the relationship between the national broadband ne...

Recently smartphone applications played an important role in many areas. One of the most important areas is business. While data is available at anytime and anywhere with the spread increasingly of broadband network, it is easy to do anything to progress your business wherever and whenever you want by using smartphone which combine the features of...

Real images may consist of many objects. These objects may be situated in different directions. Object tracking is an important process for identification of objects via the captured image. The main objective of this work is to construct an efficient information algorithm that detects the direction of objects. This algorithm is designed and impleme...

Customer data is critical to marketing success. The goal of this study is to predict customer behavior using a supervised learning neural network. Feed-forward back propagation network with tan-sigmoid transfer functions is used as a classifier to predict whether a customer will buy in this month or not. Scaled conjugate gradient (SCG) algorithm is...

Marketing campaigns of banking institutions is vital in all banks. The marketing campaigns were based on phone calls. Phone calls have an important influence in the behavior of customers. This paper proposed neural network to evaluate the bank marketing. This assessment will highlight the importance of marketing in the banks and thus the importance...

The paper focuses on national broadband network project in Jordan. In this context, His Majesty King Abdullah II has pointed Jordan in the direction of becoming a knowledge-based economy and society. So the Jordanian government constructs and operates a national broadband network. The success in the knowledge economy demands increasingly higher ski...

Artificial neural networks are a promising field in medical diagnostic applications. The goal of this study is to propose a neural network for medical diagnosis. A feed-forward back propagation neural network with tan-sigmoid transfer functions is used in this paper. The dataset is obtained from UCI machine learning repository. The results of apply...

Protection of the environment from medical waste hazards is becoming a serious problem. There is a big relation between medical waste and disease injury. The main idea of this study is predict the relation between medical wastes and diseases in Hashemite Kingdom of Jordan using Artificial Neural Networks (ANNs) model. There are six predictor parame...

Artificial neural networks are widely used in business disciplines. The objective of this study is to provide independent real estate market forecasts on home prices using artificial neural networks. The Cascade Forward Back Propagation (CFBP) neural network is used to forecast house price, based on selected 13 parameters which are considered as fo...

Bankruptcy prediction has been an important and widely studied topic. The goal of this study is to predict bank insolvency before the bankruptcy using artificial neural networks, to enable all parties to take remedial action. Artificial neural networks are widely used in finance and insurance problems. Generalized Regression Neural Network (GRNN) i...

In credit business, banks are interested in learning whether a prospective consumer will pay back their credit. The goal of this paper is to classify the credit risk which an applicant can be categorized as a good or bad consumer using artificial neural networks, to enable all parties to take remedial action. The Feed-forward back propagation neura...

Nowadays huge amounts of data are available to companies about its customers. The goal of this paper is to predict customer behavior using neural network. Artificial neural networks are widely used in business disciplines. Feed-forward back propagation neural network is used as a classifier to predict whether a customer will buy in this month or no...

Artificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Two cases are studied. The first one is acute nephritis disease; data is the disease symptoms. The second is the heart disease; data is on cardiac Single Proton Emission Compute...

Face recognition becomes an important field via the revolution in technology and computer vision. This paper concentrated on recognition rate of face recognition algorithms. The algorithms examined are: Principal Component Analysis, Two Dimensional Principal Component Analysis in Column Direction, Two Dimensional Principal Component Analysis in Row...

Predicting students’ academic performance is critical for universities because strategic programs can be planned in improving or maintaining students’ performance. The goal of this study is to predict the factors affecting the university students' performance using Artificial Neural Networks (ANN) model. Various factors that may likely influence th...

The goal of this paper is to evaluate artificial neural network in urinary diseases diagnosis. Artificial neural networks are widely used in medical problems. Artificial neural networks are used to disease diagnosis. Feed-forward back propagation neural network is used as a classifier to distinguish between infected or non-infected with two types o...

The goal of this paper is to evaluate artificial neural network in urinary diseases diagnosis. Artificial neural networks are widely used in medical problems. Artificial neural networks are used to disease diagnosis. Feed-forward back propagation neural network is used as a classifier to distinguish between infected or non-infected with two types o...

The current paper aims to predict bank insolvency before the bankruptcy using neural networks, to enable all parties to take remedial action. Artificial neural networks are widely used in finance and insurance problems. Artificial neural networks are used to predict the insolvency. The back propagation network and the Kohonen self-organizing map (S...

The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. In many fields demand for visualizing objects scanned as cross sectional slices is growing. This research has many real world applications, such as robotic environment...

The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. This research has many real world applications such as remote sensing, geology, medicine and civil. The proposed method starts with two dimensional 2D image preprocess...

In order to achieve fault tolerance, highly reliable system often require the ability to detect errors as soon as they occur and prevent the speared of erroneous information throughout the system. Thus, the need for codes capable of detecting and correcting byte errors are extremely important since many memory systems use b-bit-per-chip organizatio...

The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. This research has many real world applications such as remote sensing, geology, medicine and civil. The proposed method starts with two dimensional 2D image preprocess...

Three dimensional (3D) image visualization is one of the important processes that extract information from the given slices. The purpose of this paper deals with the 3D object visualization via two dimensional (2D) images that included many object. The main objective of this work is to find the contour of the given object in each slice and then mer...