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

This study aimed to confirm the presence of RSV using real-time PCR in nasal
and throat swabs which had no visible cytopathic effect in tissue culture technique
from adults of moderate-to-severe pneumonia with influenza-like illness. Results of
real-time RT-PCR found that viral RNA in 11.63% (5/43) of adult with pneumonia
and flu-like illness symptoms. A significant incidence of RSV infection in Dec. and
Jan. 2014 was appeared among patients aged more than 45 years. The results
showed that viral load significantly associated with disease severity. In conclusion,
multiplex RT-PCR is recommended to diagnose RSV and influenza viruses in
winter season in older patients with pneumonia and can decrease sever illness in

Diabetic retinopathy (DR) is a diabetes- caused disease that is associated with  leakage of fluid from the blood vessels into the retina, leading to its damage. It is one of the most common diseases that can lead to weak vision and even blindness. Exudates is a clear indication of diabetic retinopathy, which is the main cause of blindness in people with diabetes. Therefore, early detection of exudates is a crucial and essential step to prevent blindness and vision loss is in the analysis of digital diabetic retinopathy systems. This paper presents an improved approach for detection of exudates in retina image using supervised-unsupervised Minimum Distance (MD) segmentation method. The suggested system includes three stages; First, a

     Variations in perspective, illumination, motion blur, and weatherworn degeneration of signs may all be essential factors in road-sign identification. The current research purpose is to evaluate the effectiveness of the image processing technique in detecting road signs as well as to find the appropriate threshold value range for doing so. The efficiency of the cascade object detector in detecting road signs was tested under variations of speed and threshold values. The suggested system involved using video data to calculate the number of frames per second and creating an output file that contains the specified targets with their labels to use later in the final process (i.e., training stage). In the current research, two videos

      According to the prevalence of multidrug resistance bacteria, especially Pseudomonas aeruginosa, in which the essential mechanism of drug resistance is the ability to possess an efflux pump by which extrusion of antimicrobial agents usually occurs, this study aims to detect the presence of mexB multidrug efflux gene in some local isolates of this bacteria that show resistance towards three antibiotics, out of five. Sensitivity test to antibiotics was performed on all isolates by using meropenem (10µg/disc), imipenem (10µg/disc), amikacin (30 μg/disc), ciprofloxacin (5µg/disc) and ceftazidime (30 µg/disc). Conventional PCR results showed the presence of mexB gene (244bp) in four isolates out of t

     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

     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 EA wit

Two EM techniques, terrain conductivity and VLF-Radiohm resistivity (using two
different instruments of Geonics EM 34-3 and EMI6R respectively) have been applied to
evaluate their ability in delineation and measuring the depth of shallow subsurface cavities
near Haditha city.
Thirty one survey traverses were achieved to distinguish the subsurface cavities in the
investigated area. Both EM techniques are found to be successfiul tools in study area.