•An overlapping community finding method based on node/link information is proposed.•A new representation is introduced to encode and decode overlapping communities.•A novel two-phase mutation and a ...new double-point crossover are presented.•A metric is proposed to evaluate overlapping/non-overlapping partitions.•The proposed method shows better performance than the 15 other relevant methods.
Community detection is one of the most important and interesting issues in social network analysis. Most of the current community detection algorithms tend to find communities in social networks with just considering the topological structures of the networks. In recent years, simultaneously considering of nodes’ attributes and topological structures of social networks in the process of community detection has attracted the attentions of many scholars, and this consideration has been recently used in some community detection methods to increase their efficiencies and to enhance their performances in finding meaningful and relevant communities. But the problem is that most of these methods tend to find non-overlapping communities, while many real-world networks include communities that often overlap to some extent. In order to solve this problem, an evolutionary algorithm called MOBBO-OCD, which is based on multi-objective biogeography-based optimization (BBO), is proposed in this paper to automatically find overlapping communities in a social network with node attributes with synchronously considering the density of connections and the similarity of nodes’ attributes in the network. In MOBBO-OCD, an extended locus-based adjacency representation called OLAR is introduced to encode and decode overlapping communities. Based on OLAR, a rank-based migration operator along with a novel two-phase mutation strategy and a new double-point crossover are used in the evolution process of MOBBO-OCD to effectively lead the population into the evolution path. In order to assess the performance of MOBBO-OCD, a new metric called alpha_SAEM is proposed in this paper, which is able to evaluate the goodness of both overlapping and non-overlapping partitions with considering the two aspects of node attributes and linkage structure. Quantitative evaluations, based on three extensive experiments on 14 real-life data sets with diverse characteristics, reveal that MOBBO-OCD achieves favorable results which are quite superior to the results of 15 relevant community detection algorithms in the literature.
•A generic framework is proposed for community detection in social networks with special focus on rating-based social networks.•The framework finds the overlapping communities in which the members ...are interested in the same topic, and the strengths of their relationships are based on the rate of their viewpoints’ unity.•A novel weighting strategy for rating-based social networks is proposed which performs based on value of ratings.•Quantitative evaluations show that the proposed framework has better performance than 3 other relevant frameworks.
Owing to advances in information technology, online communications between people living in different parts of the world have considerably increased. The subsequent emergence of social networks helped this kind of communications to be further organized. One of the most important issues considered when analyzing these kinds of networks is community detection, in which a majority of studies tend to detect disjoint communities through analyzing linkages of networks. What this paper aims to achieve is to obtain overlapping communities in which the members have the same topics of interest, and where the strengths of connections between them are the consequence of their communications’ content analysis. Consequently, we have hereby proposed a generic framework for overlapping community detection in social networks with special focus on rating-based social networks. This framework considers the information shared by the users (ratings), as well as their topics of interest, for the sake of finding meaningful communities. This will lead us to topical communities in which members are interested in the same topics, and the strengths of their relationships are directly based on the rate of their viewpoints’ unity. Quantitative evaluations also reveal that the framework presented in this study achieves favorable results which are quite superior to the results of 3 other relevant frameworks in the literature.
Biogeography-based optimization (BBO) is a novel evolutionary algorithm, which is proposed with inspiration from the science of biogeography, to solve global optimization problems. To overcome the ...inability of BBO to make a good balance between its exploration and exploitation abilities, this paper introduces a new variant of BBO, which is called NBBO. The framework of NBBO considers two or more sub-iterations in an iteration of the algorithm to perform the evolution process. In each sub-iteration, a sample (sub-population) is selected from the input population of the iteration, based on a triangular probability distribution, to choose emigrating habitats (solutions) from. On the other hand, a novel two-phase migration operator is used in the framework of NBBO to make the algorithm effectively explore a search space. By making a good balance between its exploration and exploitation abilities, which is conducted by its new framework, NBBO can escape from local optima. Quantitative evaluations, based on extensive experiments on a set of 23 benchmark functions with diverse complexities, reveal that NBBO achieves favorable results which are quite superior to the results of other relevant state-of-the-art swarm intelligence-based and evolutionary algorithms.
Detecting communities in complex networks is one of the most important issues considered when analyzing these kinds of networks. A majority of studies in the field of community detection tend to ...detect communities through analyzing linkages of the networks. What this paper aims to achieve is to reach to a trade-off between similarity of nodes' attributes and density of connections in finding communities of social networks with node attributes. Since the community detection problem can be modeled as a seriously non-linear discrete optimization problem, we have hereby proposed a multi-objective discrete Biogeography Based Optimization (BBO) algorithm to find communities in social networks with node attributes. This algorithm uses the Pareto-based approach for community detection. Also, we introduced a new metric, SimAtt, to measure the similarity of node attributes in a community of a network and used it along with Modularity, which considers the linkage structure of a network to detect communities, as the two objective functions of the proposed method to be maximized. In the proposed method, a two phase sorting strategy is introduced which uses the non-dominated sorting and Crowding-distance to sort the generated solution of a population in each iteration. Moreover, this paper introduces a method for mutation probability approximation and uses a chaotic mechanism to dynamically tune the mutation probability in each iteration. Additionally, two novel strategies are introduced for mutation in unweighted and weighted networks. Since the final output of the proposed method is a set of non-dominated (Pareto-optimal) solutions, a metric named alpha_SAM is proposed to determine the best compromise solution among these non-dominated ones. Quantitative evaluations based on extensive experiments on 14 real-life data sets reveals that the method presented in this study achieves favorable results which are quite superior to other relevant algorithms in the literature.
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•Obtain the optimal surface heating for a stationary cascade turbine blade in wet steam flow by a genetic algorithm.•Nozzle efficiency (NE), integral of local entropy changes at the ...outlet (ILE), mean wetness at the outlet (MWO), mean momentum at the outlet (MMO), and cost price (CP) are objective functions.•The optimum surface heating is equal to 0.04467 (kWcm2).•In the optimal case compared to the original case, the NE and MWO are improved 0.26% and 19.94%, respectively.•In addition, ILE, MMO, and CP are degraded 0.9%, 0.32%, and 0.58%, respectively.
The purpose of this study is to obtain the optimal surface heating for a stationary cascade turbine blade in wet steam flow by a genetic algorithm. The numerical method is conducted by employing two-dimensional Navier–Stokes equations coupled with a SSTk-ω turbulence model. Nucleation and droplet growth equations are solved using the Eulerian-Eulerian approach. The numerical results show good agreement with well-established experiments. Nozzle efficiency (NE), integral of local entropy changes at the outlet (ILE), mean wetness at the outlet (MWO), mean momentum at the outlet (MMO), and cost price (CP) are objective functions. The ultimate purpose is to minimize the (ILE), (MWO), and (CP) and maximize the (NE) and (MMO) together. Since higher surface heating rates decrease MWO and MMO, while increasing ILE, CP, and NE based on optimization results, there is an optimum for the surface heating rate to gain the best performance of steam turbines. According to the numerical results, the optimum – is equal to 0.04467 (kWcm2). In the optimal case compared to the non-heat case, NE and MWO are improved 0.26% and 19.94%, respectively. In addition, the ILE and MMO are degraded 0.9%, 0.32%, respectively, and CP is estimated 0.0027 ($cm2.h).
•Optimization by GA is used to gain the suitable pitch to chord ratio for a blade.•WF, ADR, MO, PL, and IE at the exit of the cascade turbine blade are the objectives.•A pitch to chord ratio of ...Pi/AC = 0.76 is suggested.•The modified Zweifel coefficient for wet steam flow in the cascade is proposed CZF=0.62.•The wetness and radius decrease 3.59% and 1.94%, and the momentum increases 7.28%.
This study has used shape optimization by the genetic algorithm to gain the suitable pitch to axial chord ratio for a cascade turbine blade. The innovation of the present paper is the modification of the Zweifel coefficient for the wet steam flow passing through the steam turbine cascade. Wetness fraction (WF), average droplet radius (ADR), momentum (MO), pressure loss (PL), and isentropic efficiency (IE) at the exit of the cascade turbine blade in wet steam flow are selected as the objective functions. The ultimate goal was to minimize the wetness fraction, average droplet radius at the outlet of the blade, and pressure losses of the passage and maximize the efficiency and momentum at the outlet together. The Navier-Stokes equations,SSTk-ω turbulence model, and the Eulerian-Eulerian approach are applied for modeling the condensing flow. The agreement gained between the numerical results and the experimental results is satisfactory. A pitch to axial chord ratio of Pi/AC = 0.76 is suggested, and the modified Zweifel coefficient for wet steam flow in the cascade is proposed CZF=0.62. In the optimal case, the wetness fraction and the average droplet radius at the outlet decrease 3.59% and 1.94%, respectively, and the momentum increases 7.28%. In addition, the optimal case compares with original case, the isentropic efficiency decreases 2.48% and the pressure losses increases 2.15%.
Breast implants interfere may interfere with surface ECG recording. The goal of this study was to evaluate if the presence of breast implants can lead to abnormal electrocardiogram (ECG) using a ...large database in adults.
Using ICD 10 codes for breast implants and abnormal ECG, we evaluated any association between abnormal ECG coding in adult women with breast implants compared to women without breast implants utilizing the National Inpatient Sample (NIS) database. Using different age cutoffs showed similar results.
A total of 252,200 women in the NIS database had coding for abnormal EKG over age 18. There were no differences in the presence of abnormal EKG in women with or without breast implants (0.28% vs 0.3%, P = 0.64, OR: 1.02, CI: 0.72–1.32, p = 0.89). After multivariate adjustment for age, baseline characteristics, and comorbid conditions, women with or without breast implants had similar rates of abnormal ECG.
Using a large database, we could not find any effect of breast implants on ECG recording suggesting that breast implant has no significant interference with ECG.
•The optimal surface heating and droplet injection for wet steam have been obtained.•Kinetic energy, erosion, wetness, loss, and cost are considered objective functions.•The optimal case indicates an ...increase in the kinetic energy ratio by 8.68 %.•In the optimal case, erosion is reduced by 14.17 %, wetness by 2.8 %, and loss by 0.91 %.
In the last stages of the steam turbine, due to the reduction in pressure, the inlet flow is accompanied by droplets. The innovation in this study pertains to determining the optimal amount of surface heating (SH) and wetness at the inlet (WAI) using the TOPSIS method for the turbine blade cascade. In this context, three conditions have been simulated: WAI (wetness at the inlet), SH (surface heating), and simultaneously with WAI and SH. The kinetic energy ratio (KER), erosion rate ratio (ERR), wetness fraction ratio (WFR), condensation loss ratio (CLR), and cost price (CP) are considered objective functions. Navier–Stokes equations coupled with nucleation and droplet growth equations are obtained together by applying SSTk−ω. Numerical method validation is conducted with Bakhtar's data. Finally, case 1-B is proposed as the optimal case. In this case, the SH is equal to 180 (kWm2) and the average wetness fraction is equal to 1 %. The comparison of the optimal case with the original case indicates that the kinetic energy ratio is increased by 8.68 %, the erosion rate ratio is reduced by 14.17 %, the wetness fraction ratio is reduced by 2.8 %, and the condensation loss ratio is decreased 0.91 %.
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•GA optimizes superheat degree & blade pitch for maximum efficiency.•WF, MO, PL, and EC are the objective functions in the turbine blade.•The modified model to keep the inlet mass flow rate fixed is ...studied.•With the inlet steam superheat degree increasing, the condensation process weakens.•Optimization results in reduced wetness fraction, droplet radius, and pressure loss.
Steam expansion in the low-pressure stages of the steam turbines, due to the supercooled flow, causes the nucleation phenomenon and the two-phase flow, which leads to an efficiency drop and severe mechanical damage to the turbine. In this research, the impacts of the inlet steam superheat degree and variation of blade pitch in the turbine blade cascade have been investigated. Then, optimizing the concurrent effects of the inlet steam superheat degree and blade pitch to keep the inlet mass flow rate fixed are studied utilizing the genetic algorithm. Moreover, wetness fraction, pressure losses, momentum, and economic cost are the objective functions of the present study. Based on the results, as the inlet steam superheat degree increases, the inlet mass flow rate of the turbine blade decreases; and the blade pitch increase can increase the mass flow rate. Case B is chosen as the optimal case in which, when the inlet mass flow rate is fixed compared to the original case, the wetness fraction, the droplet average radius, and the pressure losses decrease by 56%, 65%, and 3.4%, respectively, and the momentum increases by 5%; in addition, the economic cost is 1.5 ($/hour) in the optimal case.
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Advanced chronic kidney disease (ACKD) is common in patients undergoing percutaneous coronary intervention (PCI). Post-PCI bleeding has been shown to increase mortality and remains an important ...challenge in these patients. Previous studies have shown increased post-PCI bleeding in CKD patients but often ACKD patients are excluded from these trials. The goal of this study was to evaluate if patients undergoing PCI with advanced renal disease have higher bleeding complications.BACKGROUNDAdvanced chronic kidney disease (ACKD) is common in patients undergoing percutaneous coronary intervention (PCI). Post-PCI bleeding has been shown to increase mortality and remains an important challenge in these patients. Previous studies have shown increased post-PCI bleeding in CKD patients but often ACKD patients are excluded from these trials. The goal of this study was to evaluate if patients undergoing PCI with advanced renal disease have higher bleeding complications.We analyzed the National Inpatient Sample (NIS) database to compare the post-PCI bleeding rates for ACKD (CKD stage 3 and above) undergoing PCI between 2006 and 2011 to those without ACKD in patients over the age of 40. Specific ICD-9 CM codes were used to identify these patients.METHODSWe analyzed the National Inpatient Sample (NIS) database to compare the post-PCI bleeding rates for ACKD (CKD stage 3 and above) undergoing PCI between 2006 and 2011 to those without ACKD in patients over the age of 40. Specific ICD-9 CM codes were used to identify these patients.A total of 49,192 patients had post-PCI bleeding during the study period of which 3,675 (7.5%) had ACKD. Patients with ACKD were older (68.7±11.7 years). During the study period, there was a decline in post-PCI bleeding rates in both ACKD and control groups. Patients with ACKD have significantly higher post-PCI bleeding rates compared to the control group. For example, in 2006, 133.9 in patients with ACKD had bleeding vs. 104.4 per 100,000 in patients without ACKD (P<0.05). After multivariate adjustment for bassline comorbidities, ACKD remained independently associated with post-PCI bleeding risk (OR: 1.07, CI: 1.03-1.11, P<0.001).RESULTSA total of 49,192 patients had post-PCI bleeding during the study period of which 3,675 (7.5%) had ACKD. Patients with ACKD were older (68.7±11.7 years). During the study period, there was a decline in post-PCI bleeding rates in both ACKD and control groups. Patients with ACKD have significantly higher post-PCI bleeding rates compared to the control group. For example, in 2006, 133.9 in patients with ACKD had bleeding vs. 104.4 per 100,000 in patients without ACKD (P<0.05). After multivariate adjustment for bassline comorbidities, ACKD remained independently associated with post-PCI bleeding risk (OR: 1.07, CI: 1.03-1.11, P<0.001).Despite the overall decline in post-PCI bleeding in patients undergoing PCI, ACKD remains independently associated with post-procedural bleeding.CONCLUSIONDespite the overall decline in post-PCI bleeding in patients undergoing PCI, ACKD remains independently associated with post-procedural bleeding.
