In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS. This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GPS devices are error-prone primarily when the receiver is located in an urban-canyons area, due to congestion and the possible interference. The outcome presents a redundancy-based model for improving the fault tolerance of IoT-based positioning systems. The simulation results show a 22.5% improvement in the fault tolerance of the IoT-based positioning system after applying the proposed validation mechanism, and a 77.4% improvement in this tolerance after applying for a more expensive module redundancy.
Industry represents a cornerstone of the process of economic development and a measure of progress and contribute to increased prosperity and high standard of living.
The researcher analyzed the productivity indicators in industrial facilities large and small at several time periods ranging from 1970 to 2009, according to the economic situation that prevailed in each period.
Different impact of periods under discussion, it made Iraq the cash surpluses during the period 70-1980 then the effects of the war after 1980 and the economic blockade since 1990, and the subsequent events of the year
... Show MoreImproving the environment is a mission that should be conducted by three associates; public authorities, environmentalists and the community. The ignorance of environmental education in Iraq has resulted to an almost environmentally illiterate community, demanding well planned programs to raise their environmental; awareness and education. On the other hand, the decision makers should be well informed about the citizens' environmental preferences to be able to set their priorities for the civil services. Merging the Iraqi citizens in listing their environmental priorities is one of many other approaches for "Environment Education" programs. Globally, such methods have proven to be effective and resulted to widespread understandin
... Show MoreThe purpose of the International Financial Reporting Standard (IFRS 15) is to determine the basis for reporting useful information to the users of financial reports on the nature, amount, timing and uncertainty about revenues and cash flows arising from a contract with a customer. It is based on specific conditions for recognizing revenue from the contract. When the two parties to the contract or one of them fulfil the performance obligations, specifically after the customer has the ability to exercise control over the product or service that is the subject of the contract. As a result of the failure of the revenue reporting requirements in the Iraqi environment to provide adequate and honestly representative information on the o
... Show MoreThe study aims to indicate the role of the mechanisms and principles of corporate governance in the activation of social responsibility reports, and increase disclosure, to achieve sustainability, legitimacy, and integrity of the business. Through the presentation of the conceptual framework for corporate governance and social responsibility, identify the key dimensions of social responsibility and the statement of the relationship between the mechanisms of governance and social responsibility reports in accordance with these dimensions. To prove the hypothesis research has selected a sample of listed companies in the Iraqi market for securities,
... Show MoreIn this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca
... Show MoreThe present study was conducted to determine histopathological changes caused by chronic effect of Nitrofurantoin(NFT) in The albino mice Testes. The Study included 40 mice were divided on the five groups: the first group taken distilled water and become control group . the remaining group which are exposure with NFT drug in concentration (100-150-200-250) mg / kg, respectively, Doses were given orally for a period (month and two months). The results of histopathological changes included occurrence of congestion in the blood vessel and degeneration of spermatogonia and aggregation of spermatids in the lumen of semineferous tubules and inhibition of spermatogensis process and decrease of sperm inside the lumen
... Show MoreIn 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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