Human Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Abstract-Servo motors are important parts of industry automation due to their several advantages such as cost and energy efficiency, simple design, and flexibility. However, the position control of the servo motor is a difficult task because of different factors of external disturbances, nonlinearities, and uncertainties. To tackle these challenges, an adaptive integral sliding mode control (AISMC) is proposed, in which a novel bidirectional adaptive law is constructed to reduce the control chattering. The proposed control has three steps to be designed. Firstly, a full-order integral sliding manifold is designed to improve the servo motor position tracking performance, in which the reaching phase is eliminated to achieve the invariance of

A new method based on the Touchard polynomials (TPs) was presented for the numerical solution of the linear Fredholm integro-differential equation (FIDE) of the first order and second kind with condition. The derivative and integration of the (TPs) were simply obtained. The convergence analysis of the presented method was given and the applicability was proved by some numerical examples. The results obtained in this method are compared with other known results.

Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

Recently, all over the world mechanism of cloud computing is widely acceptable and used by most of the enterprise businesses in order increase their productivity. However there are still some concerns about the security provided by the cloud environment are raises. Thus in this our research project, we are discussing over the cloud computing paradigm evolvement for the large business applications like CRM as well as introducing the new framework for the secure cloud computing using the method of IT auditing. In this case our approach is basically directed towards the establishment of the cloud computing framework for the CRM applications with the use of checklists by following the data flow of the CRM application and its lifecycle. Those ch

Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic