Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

This paper presents a new transform method to solve partial differential equations, for finding suitable accurate solutions in a wider domain. It can be used to solve the problems without resorting to the frequency domain. The new transform is combined with the homotopy perturbation method in order to solve three dimensional second order partial differential equations with initial condition, and the convergence of the solution to the exact form is proved. The implementation of the suggested method demonstrates the usefulness in finding exact solutions. The practical implications show the effectiveness of approach and it is easily implemented in finding exact solutions.

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This study describes how fuzzy logic control FLC can be applied to sonars of mobile robot. The fuzzy logic approach has effects on the navigation of mobile robots in a partially known environment that are used in different industrial and society applications. The fuzzy logic provides a mechanism for combining sensor data from all sonar sensors which present different information. The FLC approach is achieved by means of Fuzzy Decision Making method type of fuzzy logic controller. The proposed controller is responsible for the obstacle avoidance of the mobile robot while traveling through a map from a home point to a goal point. The FLC is built as a subprogram based on the intelligent architecture (IA). The software program  uses th

Today, data security is a major problem concerning organizations and indi- viduals. The confidentiality of information is associated with using reliable and robust encryption algorithms in systems. Cyber-attacks on data and systems have become prevalent and sophisticated, and are increasing rapidly; hence, the need for developing robust encryption algorithms is crucial nowadays. This paper proposes a new encryption algorithm using dynamic symmetric key cryptography to encrypt text files. It utilizes a secret key for encryption and decryption processes, where the key’s length is varied depending on the text size. This presented approach gives a trade-off between speed and security, making it suitable for various applications, such as secur

Nitroso-R-salt is proposed as a sensitive spectrophotometric reagent for the determination of paracetamol in aqueous solution. The method is based on the reaction of paracetamol with iron(III) and subsequent reaction with nitroso-R-salt to yield a green colored complex with maximum absorption at 720 nm. Optimization of the experimental conditions was described. The calibration graph was linear in the concentration range of 0.1 – 2.0 ?g mL-1 paracetamol with a molar absorptivity of 6.9 × 104 L mol-1 cm-1. The method was successfully applied to the determination of paracetamol in pharmaceutical preparations without any interference from common excipients. The method has been statistically evaluated with British Pharmacopoeia method a

Neuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and