Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

Image retrieval is an active research area in image processing, pattern recognition, and
computer vision. In this proposed method, there are two techniques to extract the feature
vector, the first one is applying the transformed algorithm on the whole image and the second
is to divide the image into four blocks and then applying the transform algorithm on each part
of the image. In each technique there are three transform algorithm that have been applied
(DCT, Walsh Transform, and Kekre’s Wavelet Transform) then finding the similarity and
indexing the images, useing the correlation between feature vector of the query image and
images in database. The retrieved method depends on higher indexing number. <

   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

this research is to identify the level of information awareness of the chemistry students in their fourth year studying at Ibn Al-Haytham Education College of pure sciences at the University of Baghdad. The research sample consisted of (107) male and female students out of the total number of (153) students studying during the (2017-2018) academic year, The sample therefore represents 71% of the total students. The research methodology used consisted of two parts. The first part is concerned with measuring information awareness using a multiple choice type of test related to (40) issues. The students were required to select the between (5) alternative answers for each issue. The objectives of the test and the issues used are to measure the

paid recent developments in the information and communications technology and the accompanying developments in the global market to pay particular accounting information users to demand more sophistication in terms of corporate financial reporting systems, which led to the emergence of a new type of reporting (financial reporting in real time). where is the information and communications technology mainstay Nations for the development and progress, thanks to the development of technology that have made the transmission of information easily conducted and high speed to all who need it, communication is instantaneous and the flow of information via the internet dramatically exceeded the border temporal and spatial anywhere in the w

Abstract                                                                     

This research aims to study the reflection of accounting for contingent assets and liabilities and provisions on Faithful Representation characteristic of accounting information, To achieve this goal has been questionnaire design has been distributed to research sample, which consists of (50) li

Financial markets play an important role in the economy, as it contributes to the financial and economic system of the state stability, as it reduces the adoption of the companies on the loans granted by the banks, as financial markets contribute to attracting and channeling savings to small savers who will be able to buy a number of shares proportional to their savings, It also provides them the place of exchange, and play technology and information systems an important role in facilitating exchanges and increased market activity, in this research touched on the importance of information technology in effect on the activity of the financial markets. Research is divided into three demands of the first concept of eating and the importance

Discrete   logarithms  are applied      in many    cryptographic problems  . For instance ,   in public   key .  and for construction of sets with disti nct sums of  k-clcments.  The   purpose o r  this   paper

is  to  modify  the  method ol' informationl1·iding  using        discrete logarithms  , introduce new properties of St - sets ,   uscdthe direct product   of    groups   to construct  cyclic group and finally, present modified   method   for   knapsack &