Objective: To evaluate knowledge towards smoking and its relationship with lung cancer among members of
Baghdad Nursing College.
Methodology: The study comprised 100 affiliates from the College of Nursing/ University of Baghdad that
included students, teaching staff and employees. All data was collected through a structured questionnaire
prepared by the National Cancer Research Center which were answered during a scientific symposium
organized by the center on lung Cancer Awareness in March 2016.The data were analyzed by using the SPSS,
version 22
Results: The age of the respondents ranged from (19-64 years); 76% were females and only 4% were smokers.
The results showed that the mean score for the level of knowled

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

The work in this paper focuses on the system quality of direct and coherent communication system for two computers. A system quality is represented by Signal to Noise ratio (SNR) and Bit Error Rate (BER). First part of the work includes implementation of direct optical fiber communication system and measure the system quality .The second part of the work include implementation both the( homodyne and heterodyne)coherent optical fiber communication system and measure the system quality . Laser diode 1310 nm wavelength with its drive circuit used in the transmitter circuit . A single mode of 62.11 km optical fiber is selected as transmission medium . A PIN photo detector is used in the receiver circuit. The optical D-coupler was u

This paper deals with the design and implementation of an ECG system. The proposed system gives a new concept of ECG signal manipulation, storing, and editing. It consists mainly of hardware circuits and the related software. The hardware includes the circuits of ECG signals capturing, and system interfaces. The software is written using Visual Basic languages, to perform the task of identification of the ECG signal. The main advantage of the system is to provide a reported ECG recording on a personal computer, so that it can be stored and processed at any time as required. This system was tested for different ECG signals, some of them are abnormal and the other is normal, and the results show that the system has a good quality of diagno

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition