This paper aims to study the fractional differential systems arising in warm plasma, which exhibits traveling wave-type solutions. Time-fractional Korteweg-De Vries (KdV) and time-fractional Kawahara equations are used to analyze cold collision-free plasma, which exhibits magnet-acoustic waves and shock wave formation respectively. The decomposition method is used to solve the proposed equations. Also, the convergence and uniqueness of the obtained solution are discussed. To illuminate the effectiveness of the presented method, the solutions of these equations are obtained and compared with the exact solution. Furthermore, solutions are obtained for different values of time-fractional order and represented graphically.

A robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi