Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Error (MCE) criterion was used to compare the two models, leading to the conclusion that the Nadaraya-Watson (NW) circular model outperformed the parametric model in estimating the parameters of the circular regression model. Research, Practical & Social Implications: The recommendation emphasized using the Nadaraya-Watson nonparametric smoothing method to capture the nonlinearity in the data. Originality/value: The results indicated that the Nadaraya-Watson circular model (NW) outperformed the parametric model. Paper type Research paper.
OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtain
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreIt is very necessary for the political theater to be within the space of every theatrical performance, so that the theater carries the diverse and enlightened values and cultures of this world. political theatre. In the first chapter, the researcher dealt with (the methodological framework), which includes the research problem identified by the researcher with the following question (the functional diversity of the directorial vision in the political theater)
Importance, purpose, limits and seal by defining terminology.
In the second chapter, the researcher dealt with the theoretical framework on two topics, the first (transformations of directorial vision in theatrical performance) and the second topic (aesthetic experiences i
Brain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining
... Show MoreSince the emergence of the science of international relations as an independent academic scientific field, various theories and trends have appeared and have tried to understand and explain the international reality and give a clear picture of what is happening within the international system of interactions and influences and the search for tools for stability and peace in international relations. Among these theories is the feminist theory, which is a new intellectual trend on the level of international relations theories, which tried to give an explanation of what is happening in world politics and in international relations in particular. The main issue that feminist theory is concerned with is the lack of women’s subordination
... Show MoreIn this paper a stage structure prey-predator model with Hollimg type IV functional response is proposed and analyzed. The local stability analysis of the system is carried out. The occurrence of a simple Hopf bifurcation and local bifurcation are investigated. The global dynamics of the system is investigated with the help of the Lyapunov function. Finally, the analytical obtained results are supported with numerical simulation and the effects of parameters system are discussed. It is observed that, the system has either stable point or periodic dynamics.
Education quality evaluation is one of the objectives of education quality. The evaluation includes assessing the education standards and academic program outcomes to develop intellectual, scientific and practical concepts for the educational structure. It considers the determination of the rates of the number of accepted students and graduates. The research focuses on "what are the levels of education quality according to the evaluation mechanisms in the design department" to enhance the quality system and the objectives of theoretical and applied education.
It is identifying the levels of education quality and evaluating it according to the numbers and rates of graduate students of the design department branches for morning and ev
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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