One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr

                The research aims to shed light on the importance of forensic accounting and its role in winning compensation claims against the company because of the ability of the forensic accountant (the judicial expert) to interpret and analyze the data. The research community represents the insurance companies in Iraq. The research sample was represented by the National Insurance Company. Coverage of the theoretical and deductive approach in covering the practical side, based on the financial records of the National Insurance Company for years of research.One of the most important conclusions reached by the researchers was that forensic accounting has a role

      The subject of the evolution of fire insurance of the hottest topics accidents, because it falls within the commercial insurance, as its importance is reflected for being a security source and contentment of the insured person and so it is worth pointing out the importance of fire insurance in enterprises and organizations of all kinds, because of the guarantee of its assets from meridian as well as protection from the effects of the fire therefore ensure continuity in the performance of their activities

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

Objective: The incidence of infectious diseases among hospitalized children remains high. This study describes the environmental health indicator diseases and differences between gender and age of the affected children. Patients & Methods: A review of hospitalization and death causes among children admitted to the Child Teaching Hospital for Pediatrics in Baghdad, Iraq was performed. Medical records of children admitted throughout three years period were collected for demographics data and statistical analysis using Chi-square test. Results: A total of 4,272 admissions and 309 deaths were recorded. Infectious diseases remain the primary cause of hospitalization among children and frequently lead to death; which recorded (56%) followed by ac