With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.
Objective: The aim of this study is to determine the role of spiral Computerized Tomography in the diagnosis and
detection the types of stroke.
Methodology: One hundred sixty two patients (162) (99 males and 63 females) their ages ranging from (13 – 80)
year, all of them are suffering from stroke. They were collected randomly from spiral Computerized Tomography
unit in Baquba Teaching hospital during the period from November / 2010 to December / 2011 .All the patients
were examined clinically and then done spiral Computerized Tomography examination.
Results : The results of this study showed that the stroke effected different age groups and both sex but males is
more affected than the females .The results of spiral
Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show MoreCoronavirus 2019 (COVID-19) pandemic led to a massive global socio-economic tragedy that has impacted the ecosystem. This paper aims to contextualize urban and rural environmental situations during the COVID-19 pandemic in the Middle East and North Africa (MENA) Region.
An online survey was conducted, 6770 participants were included in the final analysis, and 64% were females. The majority of the participants were urban citizens (74%). Over 50% of the urban residents significantly (
Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The sim
... Show MoreResult of studying (61) urine samples collected from students department of Biology in the College of Education-Tikrit University and the people who hold signs and symptoms of urinary tract infections with those who do not have any signs or symptoms through a questionnaire has been with the collection of samples, and the total cases were infected (39 ) cases, a rate (63.9%) distributed (28) cases a female (68.2%) and male (11) cases event rate (55%), while the distribution of positive cases among age groups have emerged group (20-22 years) is the highest rate (56%) females. The results of urine cultures accompany the presence of different types of bacteria sick and E.coli bacteria is the highest ratios positive also it is the most comm
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Semiconductor-based gas sensors were prepared, that use n-type tin oxide (SnO2) and tin oxide: zinc oxide composite (SnO2)1-x(ZnO)x at different x ratios using pulse laser deposition at room temperature. The prepared thin films were examined to reach the optimum conditions for gas sensing applications, namely X-ray diffraction, Hall effect measurements, and direct current conductivity. It was found that the optimum crystallinity and maximum electron density, corresponding to the minimum charge carrier mobility, appeared at 10% ZnO ratio. This ratio appeared has the optimum NO2 gas sensitivity for 5% gas concentration at 300 °C working temperat
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