Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

  The study was conducted to evaluate the effect of essential oil extracted from yellow peels of Citrus aurantium on the radial growth of all fungi.  Penicillium expansum, Aspergilus flavus and Fusarium oxysporum.              The results showed significant gradual reduction of the surface growth of fungi, P. expansum and A. flavus was more affected by the essential oil, while  F. oxysporum  showed less sensitivity towards the essential oil. The reaction of growth was inconcommitant with increasing concentrationsof oil, reaching concentration of (5)% which showed complete inhibition.

جريت دراسة مختبرية لمعرفة تأثير الزيت الطيار لقشور ثمار نبات النارنج الصفرC. aurantium تجاه النمو السطحي للفطريات Penicillium expansum، Aspergillus flavus و Fusarium oxysporum ، أظهرت نتائج الفعالية التثبيطية للزيت الطيار تأثيراً معنويا متفاوتاً في الفطريات المشمولة بالدراسة، إذ كان الزيت الطيار أكثر تأثيرأَ في الفطر P. expansum تلاه الفطر A. flavus ،في حين كان الفطر oxysporum F.أقل حساسية تجاه الزيت الطيار. بصورة عامة اظهر الزيت الطيار تأثيرا تثبيطيا

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

As population growth increases the demand for crops increases and their quality improves, and it becomes necessary to find innovative and modern solutions to enhance production. In this context, artificial intelligence plays a pivotal role in developing new technologies to improve crop sorting and increase agricultural yields. The present review discusses the main differences between manual and mechanical potato harvesting, explaining the advantages and disadvantages of each method. Manual harvesting is highlighted as a traditional method that allows for greater precision in handling the crop, but it requires more time and effort. In contrast, mechanical harvesting provides greater efficiency and speed in the process, but it may damage some