Image processing analysis of sigmoidal Hadamard wavelet with PCA to detect hidden object

Innovative tactics are employed by terrorists to conceal weapons and explosives to perpetrate violent attacks, accounting for the deaths of millions of lives every year and contributing to huge economic losses to the global society. Achieving a high threat detection rate during an inspection of crowds to recognize and detect threat elements from a secure distance is the motivation for the development of intelligent image data analysis from a machine learning perspective. A method proposed to reduce the image dimensions with support vector, linearity and orthogonal. The functionality of CWD is contingent upon the plenary characterization of fusion data from multiple image sensors. The proposed method combines multiple sensors by hybrid fusion of sigmoidal Hadamard wavelet transform and PCA basis functions. Weapon recognition and the detection system, using Image segmentation and K means support vector machine A classifier is an autonomous process for the recognition of threat weapons regardless of make, variety, shape, or position on the suspect’s body despite concealment

Effectiveness of an educational program on type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot

Evaluate effectiveness of educational program on type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot after applying educational program. Find out the relationship between of type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot and sociodemographic characteristics. quasi-experimental (one control group and one study group) design study, has been utilized for the current study. Study carried out in Imam AL-Hussein Medical-City. A non –probability (purposive) sample of (60) adult patients who are diagnosed with type2 diabetes mellitus these patients have met the study criteria and they are divided into two groups, (30) patients are assigned to a study group was exposed to the educational program, and (30) patients as a control group was not exposed to the educational program. Result show that mean of score of Knowledge item in Pre-test (MS=1.33) in study group, and (MS=1.35) in control group. After application Program (Post-test) study group Knowledge improve to become (MS=1.84), While control group knowledge still (MS=1.37).Conclusions: Applied educational program effectively improved the level of knowledge of the study group participants based on the findings of the study

Suport visual details of X-ray image with plain information

The objective of content-based image retrival (CBIR) is to retrieve relevant medical images from the medical database with reference to the query image in a shorter span of time. All the proposed approaches are different, yet the research goal is to attain better accuracy in a reasonable amount of time. The initial phase of this research presents a feature selection technique that aims to improvise the medical image diagnosis by selecting prominent features. The second phase of the research extracts features and the association rules are formed by the proposed classification based on highly strong association rules (CHiSAR). Finally, the rule subset classifier is employed to classify between the images. The last pert of our work extracts the features from the kidney images and the association rules are reduced for better performance. The image relevance inference is performed and finally, binary and the best first search classification is employed to classify between the images