Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

KE Sharquie, SA Al-Mashhadani, AA Noaimi, WB Al-Zoubaidi, Our Dermatology Online/Nasza Dermatologia Online, 2015 - Cited by 10

  There are many researches deals with constructing an efficient solutions for real problem having Multi - objective confronted with each others. In this paper we construct a decision for Multi – objectives based on building a mathematical model formulating a unique objective function by combining the confronted objectives functions. Also we are presented some theories concerning this problem. Areal application problem has been presented to show the efficiency of the performance of our model and the method. Finally we obtained some results by randomly generating some problems.

This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

THE ACTUAL SOCIETY MODEL

Our society model has been showing signs of exhaustion since the end of the XX century. The recent appearance of the Covid-19 virus is another consequence of humanity's distance from Nature and the environment it inhabits. Also, climate change, environmental deterioration, loss of biodiversity, overexploitation of natural resources, and social inequality are some of the consequences derived from this separation between society and Nature. We must change our operating habits. Inevitably from a society based on the market, hyper consumption, fossil energy and individual enrichment at all costs, we will have to change to another

Background: Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. Objective: The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. Methods: The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studi