Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

Back ground: The innervations of the pineal
gland from the superior cervical ganglion have
shown some form of a chromatolysis reaction.
Objective:
1-Tracing the innervations of the pineal gland by
removing the target tissue (the pineal gland in
this study) i.e. (pinealoctomy) and removal of the
superior cervical ganglion i.e. (ganglionectomy).
2- The localization and total number of the
neurons which project into the rat pineal gland
3-The effect of pinealoctomy on the SCG after a
different time interval.
Methods: Twenty five albino rats were used in
this study, Pinealoctomy was done, then after a
different time interval ganglionectomy was done,
in order to study the Chromatolysis in their cel

This paper presents the study and analysis, analytically and numerical of circular cylindrical shell pipe model, under variable loads, transmit fluid at the high velocity state (fresh water). The analytical analysis depended on the energy observation principle (Hamilton Principle), where divided all energy in the model to three parts , strain energy, kinetic energy and transmitted energy between flow and solid (kinetic to potential energy). Also derive all important equations for this state and approach to final equation of motion, free and force vibration also derived. the relations between the displacement of model function of velocity of flow, length of model, pipe thickness, density of flowed with location coordinate x-axis and angle

       In this study, light elements 19F ,22Na for  (α,n) and (n,α) reactions as well as α-particle energy  from a threshold energy  to 10 MeV are used according to the available data of reaction cross sections.  The more recent cross sections data of (α,n) and (n,α) reactions are reproduced in fine steps 86.4 KeV for 22Na (n,α) 19F  in the specified energy range, as well as cross section (α,n)  values were derived from the published data of (n,α) as a function of αenergy in the same fine energy steps by using the principle inverse reactions. This calculation involves only the ground state of  19F ,22Na in the reactions 19F (α,n) 22Na ,  2

The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we