Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any intense interest to reflect the domain knowledge. Moreover, all the published reviews did not make any direct effort to link heuristic and metaheuristic based community detection approaches, rather, they simply state them separately. The review introduced in this paper attempts to address this issue. Mainly, we review the main heuristic and metaheuristic based community detection algorithms. Then, we introduce two new taxonomies for community detection algorithms: hybrid metaheuristic and hyper heuristic that can serve as common grounds for designing a collection of new and more effective MCD algorithms. To this end, we introduce four new systematic frameworks integrating both heuristic and metaheuristic algorithms, illustrating the possible issues that would fuel the desire for researchers to direct their future interest towards developing more effective community detection instances from the context of these frameworks.
It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
... Show MoreFeature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreIn this work, we focused on studying 1,4-naphthoquinones and their derivatives, and knowing the methods of preparing them using different auxiliary agents and forming derivatives containing heterocyclic rings, active groups and saturated rings containing heterogeneous elements . In addition, due to their strong antibacterial, antifungal and anticancer activity, 1,4-naphthoquinone compounds biological importance and are considered a source of various pharmaceutical compounds.
There is no access to basic sanitation for half the world's population, leading to Socioeconomic issues, such as scarcity of drinking water and the spread of diseases. In this way, it is of vital importance to develop water management technologies relevant to the target population. In addition, in the separation form of water treatment, the compound often used as a coagulant in water treatment is aluminum sulfate, which provides good results for raw water turbidity and color removal. Studies show, however, that its deposition in the human body, even Alzheimer's disease, can cause serious harm to health and disease development. The study aims to improve the coagulation/flocculation stage related to the amount of flakes, i
... Show MoreThe study aimed to monitor the concept of reputation in the previous literature, its relationship to mental image and identity, and to reveal recent trends in its measurement Techniques.
The study relied on a descriptive approach using library survey and comparative analysis, and the study reached following conclusions:
Despite the beginning of the first signs of reputation In the fifties of the last century, however, Defining and standardizing the concept with clear and specific dimensions began in the 1990s and the beginning of the third millennium. The concept of reputation refers to the stakeholders’ overall evaluation of organizations, which reflects their perceptions of
... Show MoreTremendous efforts have been exerted to understand first language acquisition to facilitate second language learning. The problem lies in the difficulty of mastering English language and adapting a theory that helps in overcoming the difficulties facing students. This study aims to apply Thomasello's theory of language mastery through usage. It assumes that adults can learn faster than children and can learn the language separately, and far from academic education. Tomasello (2003) studied the stages of language acquisition for children, and developed his theory accordingly. Some studies, such as: (Ghalebi and Sadighi, 2015, Arvidsson, 2019; Munoz, 2019; Verspoor and Hong, 2013) used this theory when examining language acquisition. Thus,
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The performance of job effectively requires narrowing the meaningful routine activities and attempting employing the job procedures in favor of public welfare through adding the green impact as well as removing them from the red tapes which reflect the firmness of procedures, to enable the job parties to make their job independently, and pushing them to gain priority in the competition layer. This is not attaining easily amidst the regulatory problems expressed by the complication of procedures, the thing which make identifying the problem of the study through the following question:
Should we make the complex of procedures and their firmness a way to adopt the idea of the green regulatory tapes supportin
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