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, and Pneumonia) classification tasks. Our model has achieved an accuracy value of 98.4% for binary and 93.8% for the multi-class classification. The number of parameters of our model is 11 Million parameters which are fewer than some state-of-the-art methods with achieving higher results.
This paper presents a novel idea as it investigates the rescue effect of the prey with fluctuation effect for the first time to propose a modified predator-prey model that forms a non-autonomous model. However, the approximation method is utilized to convert the non-autonomous model to an autonomous one by simplifying the mathematical analysis and following the dynamical behaviors. Some theoretical properties of the proposed autonomous model like the boundedness, stability, and Kolmogorov conditions are studied. This paper's analytical results demonstrate that the dynamic behaviors are globally stable and that the rescue effect improves the likelihood of coexistence compared to when there is no rescue impact. Furthermore, numerical simul
... Show MoreThe developing countries can be distinguished by spatial disparities and by this a wide gap between urban and rural settlements were produced as well as the appearance of primate cities. The effect of spatial development as a dynamic and continuous process can be perceived in the state of population distribution inside settlements inter and intra regions as well as the hierarchy of urban settlements according to time series. The research proved that the improvement judgment of the structure of the urban system using Gene factor is not accurate because it cannot be accounted for the internal components of the system which make a contrariety between the whole judgment (country) and partial components (Provinces including Sulaimaniy
... Show MoreSemantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po
The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
... Show MoreThe primary objective of the present research is to diagnose the most mportant imensions of quality of work life in a sample of individuals working in the Northern Gas Filling Company in Nynawa. The study sample consisted of 140 employees of the Northern Region Filling Company in even ,Through a questionnaire prepared for this purpose. The study concluded that there are five main factors that are considered to be measure of the quality of working life and are based on their importance: Empowerment, organizational health, internal work environment, motivation, development and training of workers. The study recommended that the organization should payattentio
... Show MoreThe main aim of this paper are the design and implementation of a pharmaceutical inventory database management system. The system was implemented by creating a database containing information about the stored medicines in the inventory, customers making transactions with the pharmaceutical trading company (which owns the inventory), medical suppliers, employees, payments, etc. The database was connected to the main application using C sharp. The proposed system should help in manag inginventory operations which include adding/updating employees’ information, preparing sale and purchase invoices, generating reports, adding/updating customers and suppliers, tracking customer payments and checking expired medicines in order to be disposed
... Show MoreSCADA is the technology that allows the operator to gather data from one or more various facilities and to send control instructions to those facilities. This paper represents an adaptable and low cost SCADA system for a particular sugar manufacturing process, by using Programmable Logic Controls (Siemens s7-1200, 1214Dc/ Dc/ Rly). The system will control and monitor the laboratory production line chose from sugar industry. The project comprises of two sections the first one is the hardware section that has been designed, and built using components suitable for making it for laboratory purposes, and the second section was the software as the PLC programming, designing the HMI, creating alarms and trending system. The system will ha
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
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