Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algorithms have been implemented to unfold the structures of communities, the influence of NMI on the Q, and vice versa, between a detected partition and the correct partition in signed and unsigned networks is unclear. For this reason, in this paper, we investigate the correlation between Q and NMI in signed and unsigned networks. The results show that there is no direct relationship between Q and NMI in both types of networks.
The research problem was to identify the impact of monetary policies on economic growth in the oil and non-oil countries. The researcher chose the Republic of Iraq as an example for the oil countries and the Arab Republic of Egypt as an example for the non-oil countries to hold a comparison on the impact of monetary policies.
The research found that the monetary policies and their tools in the Iraqi economy affect the rate of GDP growth by 73%, which shows the strong impact of monetary policies on the economic growth in the Iraqi economy as an example of an oil state. GDP growth rate of 61%, indicating the impact of monetary policies on economic growth in the
النظام السياسي اليمني : دراسة في المتغيرات الداخلية
The current research aims to identify the most important green productivity tools GPT and the possibility of applied in industrial companies in general and the companies operating in the province of Nineveh, in particular, as well as the study of some personality characteristics and functional, which is believed to be an impact on the application of these tools in industrial companies. Accordingly, the research community of managers in the company of medicines and medical supplies ready-made clothes _ operating in the province of Nineveh, who are (80) while the manager was subjected to research procedures (49) Director representing (61.25%)
... 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 MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreDust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so
... Show MoreCiprofloxacin, which is a second generation of fluoroquinolone and one of the most effective and widely used drugs within fluoroquinolone. Unfamiliar adverse effects of ciprofloxacin such as bone marrow (BM) suppression, thrombocytopenia, anemia, agranulocytosis, renal failure, and others observed. Lutein, is a xanthophyll (an oxygenated carotenoid), was focused by most studies as it has a strong antioxidant activity in vitro; and also, it has been associated with reducing the risk of the age-related disorders. The current study was designed to describe the role of apoptosis through the measurement of Bcl-2 associated X protein (Bax) marker, as mechanisms of bone marrow toxicity induced by ciprofloxacin and to find whether lutei
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