A confluence of forces has brought journalism and journalism education to a precipice. The rise of fascism, the advance of digital technology, and the erosion of the economic foundation of news media are disrupting journalism and mass communication (JMC) around the world. Combined with the increasingly globalized nature of journalism and media, these forces are posing extraordinary challenges to and opportunities for journalism and media education. This essay outlines 10 core principles to guide and reinvigorate international JMC education. We offer a concluding principle for JMC education as a foundation for the general education of college students.

In this article, the numerical and approximate solutions for the nonlinear differential equation systems, represented by the epidemic SIR model, are determined. The effective iterative methods, namely the Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM), and the Banach contraction method (BCM), are used to obtain the approximate solutions. The results showed many advantages over other iterative methods, such as Adomian decomposition method (ADM) and the variation iteration method (VIM) which were applied to the non-linear terms of the Adomian polynomial and the Lagrange multiplier, respectively. Furthermore, numerical solutions were obtained by using the fourth-orde Runge-Kutta (RK4), where the maximum remaining errors showed th

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

many painters tried to mix colors with Music by direct employment through colorful musical pieces or the use of multiple instruments and techniques , or vice versa, including the French artist )Robert Stroben(, he transferred the piece of music to be depicted on the painting and worked on the tones of music (Johann Sebastian Bach) by dropping the color on the lines of the musical scale, for example (the C tone) ranging from brown to red ( Tone La A) from gray to orange, and so on, the presence of links and similarity factors between the world of music and the world of colors facilitated the process of linking musical notes with colors, the most famous of which was presented by the world (Newton) in the circle of basic colors and linking

     In this study, we propose a suitable solution for a non-linear system of ordinary differential equations (ODE) of the first order with the initial value problems (IVP) that contains multi variables and multi-parameters with missing real data. To solve the mentioned system, a new modified numerical simulation method is created for the first time which is called Mean Latin Hypercube Runge-Kutta (MLHRK). This method can be obtained by combining the Runge-Kutta (RK) method with the statistical simulation procedure which is the Latin Hypercube Sampling (LHS) method. The present work is applied to the influenza epidemic model in Australia in 1919  for a previous study. The comparison between the numerical and numerical simulation res

هناك عوامل عديدة تؤثر في البنية الشكلية للم ا ركز الحضرية التي تشهد تحولات وبصورة مستمرة ومع
توسع المدينة ونموها تفقد هذه الم ا ركز لمقومات بنيتها الحضرية المتكاملة بسبب تلك التحولات الحاصلة
ضمنه وبصورة ديناميكية من اضافات وتغيرات في النمط الحضري الذي يتشكل من عدة نماذج معمارية
جديدة مؤثرة ولأجل ذلك جاء البحث لايضاح اثر هذه العلاقة بين النمط الحضري والنموذج المعماري
وتحولاته في تكاملية البنية ا

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

      In this paper, we are mainly concerned with estimating cascade reliability model (2+1) based on inverted exponential distribution and comparing among the estimation methods that are used . The maximum likelihood estimator and uniformly minimum variance unbiased estimators are used to get  of the strengths  and the stress ;k=1,2,3 respectively then, by using the unbiased estimators, we propose Preliminary test single stage shrinkage (PTSSS) estimator when a prior knowledge is available for the scale parameter as initial value due past experiences . The Mean Squared Error [MSE] for the proposed estimator is derived to compare among the methods. Numerical results about conduct of the considered

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r