Implementation of variational iteration method for various types of linear and nonlinear partial differential equations

There are various linear and nonlinear one-dimensional partial differential equations that are the focus of this research. There are a large number of these equations that cannot be solved analytically or precisely. The evaluation of nonlinear partial differential equations, even if analytical solutions exist, may be problematic. Therefore, it may be necessary to use approximate analytical methodologies to solve these issues. As a result, a more effective and accurate approach must be investigated and analyzed. It is shown in this study that the Lagrange multiplier may be used to get an ideal value for parameters in a functional form and then used to construct an iterative series solution. Linear and nonlinear partial differential equations may both be solved using the variational iteration method (VIM) method, thanks to its high computing power and high efficiency. Decoding and analyzing possible Korteweg-De-Vries, Benjamin, and Airy equations demonstrates the method’s ability. With just a few iterations, the produced findings are very effective, precise, and convergent to the exact answer. As a result, solving nonlinear equations using VIM is regarded as a viable option

A framework of a route optimization scheme for nested mobile network

Network mobility technology is now being accomplished with the foundation of NEMO (NEtwork MObility), developed by Internet Engineering Task Force (IETF). Although, it achieves optimal and continuous communication, it still suffers from some limitations, especially when the level of nesting increases. To overcome these drawbacks, this paper will present a route optimization framework for nested mobile network using hierarchical structure with Binding Update Tree (BUT). This framework should reduce packet overhead, handoff latency, packet transmission delay, and achieve optimal routing. At last, a comparison will be done with bi-directional tunneling used by NEMO Basic Support to evaluate the performance of the proposed framework

Cognitive dysfunction in naturally occurring canine idiopathic epilepsy

Globally, epilepsy is a common serious brain disorder. In addition to seizure activity, epilepsy is associated with cognitive impairments including static cognitive impairments present at onset, progressive seizure-induced impairments and co-morbid dementia. Epilepsy occurs naturally in domestic dogs but its impact on canine cognition has yet to be studied, despite canine cognitive dysfunction (CCD) recognised as a spontaneous model of dementia. Here we use data from a psychometrically validated tool, the canine cognitive dysfunction rating (CCDR) scale, to compare cognitive dysfunction in dogs diagnosed with idiopathic epilepsy (IE) with controls while accounting for age. An online cross-sectional study resulted in a sample of 4051 dogs, of which n = 286 had been diagnosed with IE. Four factors were significantly associated with a diagnosis of CCD (above the diagnostic cut-off of CCDR ≥50): (i) epilepsy diagnosis: dogs with epilepsy were at higher risk; (ii) age: older dogs were at higher risk; (iii) weight: lighter dogs (kg) were at higher risk; (iv) training history: dogs with more exposure to training activities were at lower risk. Impairments in memory were most common in dogs with IE, but progression of impairments was not observed compared to controls. A significant interaction between epilepsy and age was identified, with IE dogs exhibiting a higher risk of CCD at a young age, while control dogs followed the expected pattern of low-risk throughout middle age, with risk increasing exponentially in geriatric years. Within the IE sub-population, dogs with a history of cluster seizures and high seizure frequency had higher CCDR scores. The age of onset, nature and progression of cognitive impairment in the current IE dogs appear divergent from those classically seen in CCD. Longitudinal monitoring of cognitive function from seizure onset is required to further characterise these impairments

Route optimization scenario of a new scheme based on nested mobile network

With the rapid growth of wireless technologies and increasing number of mobile digital devices, mobility has been an important element on the Internet. NEMO Basic Support, designed by the Internet Engineering Task Force (IETF) to provide network mobility, is not efficient to offer low latency handoff in the case of nested mobile networks because it produces a long transfer delay and excessively large packet sizes due to non-optimal routes and multiple encapsulations. This paper presents a route optimization scenario for nested mobile network using hierarchical structure with Binding Update Tree (BUT). This scheme should reduce packet overhead, handoff latency, packet transmission delay, and achieve optimal routing

Analytical evaluation of a new route pptimization scheme for nested mobile network

As the Internet becomes more and more accessible, claims for mobility are not limited anymore to single hosts. Supporting networks’ roaming that move as one entity is required in order to enable the transparency of Internet in mobile platforms, like cars, trains, planes, buses, etc. To accomplish this, NEMO Basic Support has been proposed and developed by the Internet Engineering Task Force (IETF) in order to provide an efficient communication. Nevertheless, NEMO still suffers from some limitations, especially in case of nested mobile network. This paper presents new route optimization scheme for nested mobile network using hierarchical structure with Binding Update Tree (BUT). This framework should reduce packet overhead, handoff latency, packet transmission delay and achieve optimal routing. Lastly, this paper will compare analytically between bi-directional tunnelling used by NEMO BS and route optimization of the proposed scheme