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.
In the name of God, praise be to God, and prayers and peace be upon the best of God’s creation, Muhammad bin Abdullah, and upon his family and companions, and from his family:
And after:
He saw from verbs that transcend one effect if it is visual and to two effects if it is heart and this action has several strokes and it is an awareness of the sense and illusion and imagination and reason and in addition to that it has many meanings dealt with in the glossary books and as for what the verb included in the audio studies it is the explanation and deletion and slurring The heart of my place. As for what the grammatical studies included, it focuses on one or two effects according to its l
The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a
... Show MoreDuring recent years, there has been an increasing interest in the investigation of the cytokines roles in pathogenesis of cancer, thus the study aimed at evaluating the level of tumor necrosis factor-alpha(TNF-?) in sera of Iraqi multiple myeloma (MM) patients. Beta 2-microglobulion (?2-m) was assessed to determine if there was any association between this cytokine and the level of ?2- m, as the latter is related to the stage of the disease. In addition, the age and gender were also taken into consideration. Furthermore, we investigated the relationship between IgG and TNF-? in sera of patients. 49 Iraqi patients (27 males and 22 females).The patients were also divided into two groups: the first group included (17) patients who were
... Show MoreThe hydrodynamics behavior of gas - solid fluidized beds is complex and it should be analyzed and understood due to its importance in the design and operating of the units. The effect of column inside diameter and static bed height on the minimum fluidization velocity, minimum bubbling velocity, fluidization index, minimum slugging velocity and slug index have been studied experimentally and theoretically for three cylindrical columns of 0.0762, 0.15 and 0.18 m inside diameters and 0.05, 0.07 and 0.09 m static bed heights .The experimental results showed that the minimum fluidization and bubbling velocities had a direct relation with column diameter and static bed height .The minimum slugging velocity had an
... Show MoreThis study aimed to see how allicin (45mg/kg BW) affected diabetic Mellitus in male rats (DM). Forty male rats were utilized, and they were split into four groups at random for 42 days. T2 was treated with 45 mg/kg B.W of allicin dissolved in 1 ml of D.W daily and injected with a single dose of sodium citrate buffer (0.5ml Intra-Peritoneal IP), DM was induced in T1 and T2 by injection of a single dose of streptozotocin 50 mg/kg B.W IP, T1 was assigned as a positive control, T3 received 45 mg/kg B.W. of allicin dissolved in 1 ml D.W. every day, and a single dose of sodium citrate buffer was injected (0.5ml IP). When diabetic rats treated with allicin in T2 were compared to diabetic rats in T1, the findings indicated a significant increase (P
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This study deals with the influence of the industrial buyer behavior in Channels of distribution. It concentrates on one section of management levels in the company. Which is that of administrative managers The research problem is attempt to study and analysis the influence of industrial buyer behavior in channels of distribution.. The aiming at achieving a number of applicable goals depending on one major hypotheses I set a questionnaire in collecting the data and information relating to the study، which was distributed to sample of ( 30) department manager heads of section states company . In order to process the data resorted to many statistical methods such as arithmetic means the sta
... Show MoreDetection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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