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Intelligent Dust Monitoring System Based on IoT
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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 train and test part was applied to dust phenomena historical data. Its data has been collected through the Iraqi Meteorological Organization and Seismology (IMOS) raw dataset with 170237 of 17023 rows and 10 columns. The LSTM model achieved small time, computationally complexity of, and layers number while being effective and accurate for dust prediction. The simulation results reveal that the model's mean square error test reaches 0.12877 and Mean Absolute Error (MAE) test is 0.07411 at the same rates of learning and exact features values of vector in the dense layer, representing a neural network layer deeply is connected to the LSTM training proposed model. Finally, the model suggested enhances monitoring performance.

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Clarifying Optimum Setting Temperatures and Airflow Positions for Personal Air Conditioning System on Flight
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In recent years, the demand for air travel has increased and many people have traveled by plane. Most passengers, however, feel stressed due to the limited cabin space. In order to make these passengers more comfortable, a personal air-conditioning system for the entire chair is needed. This is because the human body experiences discomfort from localized heating or cooling, and thus, it is necessary to provide appropriate airflow to each part of the body. In this paper, a personal air-conditioning system, which consists of six vertically installed air-conditioning vents, will be proposed. To clarify the setting temperature of each vent, the airflow around the passenger and the operative temperature of each part of the body is investigate

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Publication Date
Sun Dec 05 2010
Journal Name
Baghdad Science Journal
Effect of parasites on the of digestive system in Iraqi bulbul Pycnonotus lecuotis mesoptamiae
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This study included collecting of 150 specimens of the Iraqi Bird Bulbule Pycnonotus lecuotis mesoptamiae (Pycnotidae , Passeriformes), from the 1st of November 2004 to 30th of October 2005 in the city of Baghdad and its suburbs, in concern of identifying the internal parasite of the digestive tract of these birds and studying the diseases resulted from the infection. The study showed that the bird Bulbule is Parasitized by Four types of Cestodes ,two of them are recorded in this kind of bird in Iraq for the first time ,Paradicranotinae anormalis and Haploparaxis sp. , and the other two are Raillietina tetragona and Allohymenolepsis sp. ,and by two types of Pin Worm(Trematode) that are identified for the first time in the Bird Bulb

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Publication Date
Sun Sep 11 2022
Journal Name
Mathematics
Modeling and Analysis of the Influence of Fear on a Harvested Food Web System
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The food web is a crucial conceptual tool for understanding the dynamics of energy transfer in an ecosystem, as well as the feeding relationships among species within a community. It also reveals species interactions and community structure. As a result, an ecological food web system with two predators competing for prey while experiencing fear was developed and studied. The properties of the solution of the system were determined, and all potential equilibrium points were identified. The dynamic behavior in their immediate surroundings was examined both locally and globally. The system’s persistence demands were calculated, and all conceivable forms of local bifurcations were investigated. With the aid of MATLAB, a numerical simu

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Designand Implementation of New DES64X and DES128X on 32, 64 Bit Operating System Environments
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In this paper, a description of a design for new DES block cipher, namely DES64X and DES128X. The goals of this design, a part of its security level, are large implementation flexibility on various operating systems as well as high performances. The high level structure is based on the principle of DES and Feistel schema, and proposes the design of an efficient key-schedule algorithm which will output pseudorandomsequences of subkeys. The main goal is to reach the highest possible flexibility, in terms of round numbers, key size, and block size. A comparison of the proposed systems on 32-bit, 64-bit operating system, using 32-bit and 64-bit Java Virtual Machine (JVM), showed that the latter has much better performance than the former.

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Publication Date
Sat Jun 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Annealing on the Crystallization of Poly Vinyl Chloride for Drug Delivery System
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Poly vinyl alcohol has been studied for its ability to form crystallites by using annealing method. Semicrystalline films of poly vinyl alcohol (PVA) were prepared by casting 11.5 wt. % and 13 wt. % PVA aqueous solution onto glass slides at annealing temperature range 90 -120°C and duration time 15- 60 minute. This allowed the macromolecules to form crystallites, small regions of folded and compacted chains separated by amorphous regions where single PVA chain may pass through several of these crystallites. Degree of crystallinity of PVA films (hydrogels) was determined by method of density; on the other hand the swelling behavior was conducted by the determination of water uptake, wet degree of crystallinity, gel fraction and solu

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Tue Jun 24 2025
Journal Name
Baghdad Science Journal
Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
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Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

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Publication Date
Fri Oct 02 2009
Journal Name
Noise And Health
Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach
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Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Improving the Durability of Streak and Thermal Insulation of Petroleum Pipes by Using Polymeric Based Paint System: Polymer Matrix Composites have several and wide applications
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This research deals with increasing the hardening and insulating the petroleum pipes against the conditions and erosion of different environments. So, basic material of epoxy has been mixed with Ceramic Nano Zirconia reinforcement material 35 nm with the percentages  (0,1,2,3,4,5) %, whereas the paint basis of broken petroleum pipes was used  to paint on it, then it was cut into dimensions (2 cm. × 2 cm.) and 0.3cm high. After the paint and percentages are completed, the samples were immersed into the paint. Then, the micro-hardness was checked according to Vickers method and thermal inspection of paint, which contained (Thermal conduction, thermal flux and Thermal diffusivity), the density of the painted samples was calculate

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