In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and hard optimization problem. One of the main difficulties in identifying overlapping protein complexes is the accuracy of the partitioning results. In order to accurately identify the overlapping structure of protein complexes, this paper has proposed an overlapping complex detection algorithm termed OCDPSO-Net, which is based on PSO-Net (a well-known modified version of the particle swarm optimization algorithm). The framework of the OCDPSO-Net method consists of three main steps, including an initialization strategy, a movement strategy for each particle, and enhancing search ability in order to expand the solution space. The proposed algorithm has employed the partition density concept for measuring the partitioning quality in PPI network complexes and tried to optimize the value of this quantity by applying the line graph concept of the original graph representing the protein interaction network. The OCDPSO-Net algorithm is applied to a Collins PPI network and the obtained results are compared with different state-of-the-art algorithms in terms of precision ( ), recall ( ), and F-measure ( ). Experimental results confirm that the proposed algorithm has good clustering performance and has outperformed most of the existing recent overlapping algorithms. .
The research topic (The dramatic structure transformations in the Iraqi Feature Film) studies the dramatic structure and its transformations in the Iraqi feature film. The research determined the research problem and the need for it in addition to the aims and the limits of the study as well as its importance. The theoretical framework consists of the following themes: the dramatic transformations mechanism and dramatic data in the Iraq film 1957-2003 then the dramatic values transformations and the performance contradictions in the Iraqi film.
The research, after concluding the theoretical framework, came up with a number of indicators of the theoretical framework that have been used as a tool to analyze the sample. The research proc
The presence of a single complex adaptive weight in each element channel of an adaptive array antenna is sufficient for processing of narrowband signals. The ability of an adaptive array antenna to null interference deteriorates rapidly as the interference bandwidth increases. The performance of narrowband adaptive array antenna with LMCV Beamforming algorithm is examined. The interaction effects between received signal angle of arrival and array parameters like the interelement spacing and the number of array element and the received signal bandwidth were studied. The output Signal to Interference plus Noise Ratio (SINR) and Interference to Noise Ratio (INR) are used as performance parameters for evaluation of these effects. It is found
... Show MoreA nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThe meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
... Show MoreThe nuclear structure of some cobalt (Co) isotopes with mass number A=56-60 has been studied depending on the effect of some physical properties such as the electromagnetic properties effects, such as, elastic longitudinal form factors, electric quadrupole moments, and magnetic dipole moments. The fp model space is used to present calculations using GXFP1 interaction by adopting the single particle wave functions of the harmonic oscillator. For all isotopes under consideration, the 40Ca nucleus is regarded as an inert core in fp model-space, while valence nucleons are moving through 1f7/2, 2p3/2, 1f5/2, and 2p1/2 orbits. The effects of core-polarization are obtained by the first orde
... Show MoreIn this work, porous Silicon structures are formed with photochemical etching process of n-type Silicon(111) wafers of resistivity (0.02.cm) in hydrofluoric acid (HF) of concentration (39%wt) under light source of tungeston halogen lamp of (100 Watt) power. Samples were anodized in a solution of 39%HF and ethanol at 1:1 for 15 minutes. The samples were realized on n-type Si substrates Porous Silicon layers of 100m thickness and 30% of porousity. Frequency dependence of conductivity for Al/PSi/Si/Al sandwich form was studied. A frequency range of 102-106Hz was used allowing an accurate determination of the impedance components. Their electronic transport parameters were determined using complex impedance measurements. These measu
... Show More