This research a mining at evaluation the efficiency of the nursing performance depended on standards of W.H.O. via application standards of W.H.O on the nursing personnel in medical city office,  in light of it, it has design  world evaluation list, and a sample was chosen  from the nursing personnel in  given researched the organization whom they are evaluated according to the standards of W.H.O for the nursing performance included of ten standards, divided in to 45 question , besides the evaluation list, the researcher get assistance of some tools of collection information via  actual checking and personal interviews, a number of statistical means were used to manipulate t

N/A

Objective: the aim of this study is to determine the level of students' knowledge about the environmental health.
Methodology: The cross-sectional study was conducted at the College of Health and Medical Technology in Baghdad
city during the period from 1st march till 1st of July 2012. Data was collected by self-recording of a previously designed
questionnaire to obtain socio-demographic information such as (age, gender, department, year of grade).
Results: The highest rate of students were in the 2nd year followed by the 3rd year, highest rate of students had low
level of knowledge followed by intermediate level of knowledge, while lowest rate of students on had high level of
knowledge .Females had higher level of know

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le