Scams remain among top cybercrime incidents happening around the world. Individuals with high susceptibility to persuasion are considered as risk-takers and prone to be scam victims. Unfortunately, limited number of research is done to investigate the relationship between appeal techniques and individuals' personality thus hindering a proper and effective campaigns that could help to raise awareness against scam. In this study, the impact of fear and rational appeal were examined as well as to identify suitable approach for individuals with high susceptibility to persuasion. To evaluate the approach, pretest and posttest surveys with 3 separate controlled laboratory experiments were conducted. This study found that rational appeal treatm

This paper set forth the spatial suitability of the informal settlement supposed to be distributed by the Iraqis government to poor people. The Iraqi government identified 9 locations of informal settlement in Baghdad city and acceptance it as a reality as a help for them to getting home. In this paper I discovered the suitability of those locations which one will be suitable more than others for living. The analysis process was applied using the GIS environment – spatial analysis. According to the results, It has been identified as the most important measures to identify which one of these areas suitable for development for housing by using some criteria (Distance from the city center, Proximity from transport routes, Proximity of high v

      This study is concerned with organizational learning and its impact on total quality management in the education sector. Organizational learning is a process that provides the educational sector with the ability to adapt and respond rapidly to developments and changes in a better way according to its main dimensions (Mental Models, Personal Mastery, Team Learning, Shared Vision, System Thinking) by adopting the philosophy of Total Quality Management (TQM) in accordance with its basic dimensions (leadership, customer satisfaction, participation of workers, continuous improvement, training and education). The main purpose of this study is to know (the impact of the Senge model of organizational learni

      This study is concerned with organizational learning and its impact on total quality management in the education sector. Organizational learning is a process that provides the educational sector with the ability to adapt and respond rapidly to developments and changes in a better way according to its main dimensions (Mental Models, Personal Mastery, Team Learning, Shared Vision, System Thinking) by adopting the philosophy of Total Quality Management (TQM) in accordance with its basic dimensions (leadership, customer satisfaction, participation of workers, continuous improvement, training and education). The main purpose of this study is to know (the impact of the Senge model of organizational learni

         The aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In