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

An experiment was carried out to study the effects of Time Factor, potassium and Molybdenum on Rhizobium growth. The objective of the experiment, which conducted under laboratory conditions, was to investigate the interaction effects of using three levels of Molybdenum (0, 0.25, 2.50 mg Mo . Kg-1 sterile soil) and four levels of potassium (0, 25, 50, 100 mg K . Kg-1 sterile soil) on the viable counts of Rhizobium growth in the sterile soil after 3, 9, 15 and 21 days of incubation at 28°C. The results indicated that Molybdenum level 2.50 mg Mo . Kg-1 sterile soil and potassium level 50 mg K . Kg-1 sterile soil recorded the biggest significant increase in the viable counts of Rhizobium growth in the sterile soil especially after 15 da

     NS-2 is a tool to simulate networks and events that occur per packet sequentially based on time and are widely used in the research field. NS-2 comes with NAM (Network Animator) that produces a visual representation it also supports several simulation protocols. The network can be tested end-to-end. This test includes data transmission, delay, jitter, packet-loss ratio and throughput. The Performance Analysis simulates a virtual network and tests for transport layer protocols at the same time with variable data and analyzes simulation results based on the network simulator NS-2.

Abstract:

The main objective of the research is to build an optimal investment portfolio of stocks’ listed at the Iraqi Stock Exchange after employing the multi-objective genetic algorithm within the period of time between 1/1/2006 and 1/6/2018 in the light of closing prices (43) companies after the completion of their data and met the conditions of the inspection, as the literature review has supported the diagnosis of the knowledge gap and the identification of deficiencies in the level of experimentation was the current direction of research was to reflect the aspects of the unseen and untreated by other researchers in particular, the missing data and non-reversed pieces the reality of trading at the level of compani

The study aims at finding out the effect of the lead time strategy on the first intermediate class pupils' achievement in geography The partial experimental design of two groups, experimental and control, with pre-post tests is used. The sample is represented in (73) female pupils. The sample is divided into two groups (37) experimental group and (36) control one. The sam ple is selected from first intermediate class pupils ( Al Batol intermediate school for girls) Baghdad Al-karkh-3, for academic year 2015-2016 The researcher has equalized the two groups in several variables: the previous achievement tests, intelligence, age in months, the scores of geography test of first course

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

A computer theoretical s1udy has been carried out in field of opto - clcctroniccs, to design  an electron  gun using the space charge effect.

The   distribution  of   axial  potential    upon   the  two   -electrode

immersion  lens  of  (L=l4mm)  has been  carried   out   using   Poisons equation and the  tinite  clement  method;  knowing  the first 11nd second derivation  of  the    axial   potential   and  the  solution   of  paraxial   ray equation, the  optical   prop