Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent

The study included 200 samples were collected from children under two years included (50 samples from each of Cerebrospinal fluid, Blood, Stool and Urine) from, (Central Children Hospital and Children's Protections Educational Hospital) The Iraqi Ministry of Health, the Department of Health Baghdad .the period from the first of 2015 September to the first of December 2015, Were obtained isolates bacterial subjected to the cultural, microscopic and biochemical examination and diagnosed to the species by using vitek2 system .The results showed there were contamination in 6.5% of clinical samples. The diagnosed colonies which gave pink color on the MacConkey agar, golden yellow color on the Trypton Soy agar and green color on t

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so