When industrial and  constructional renaissance started in the world, the great interest was going on towards the equipment’s,  which was the first mean for production. After industry was settled the interest was going on towards the men ship which manpower on which the production depends. It was approved that it represents the basic part in all of the processes and the protection of those individuals against dangers of these equipment’s, industry and its accidents was the basic things which was studied in many researches until it crystallized in general principles for all industries and other take care in each industry.

     The professional safety is concerned as restrict which

Abstract The avulsion of the flexor digitorum profundus, also known as the jersey finger, is a well-known injury that can be treated surgically. It has been classified into four types, among them type IV which involves tendon avulsion from an associated bony fragment with subsequent retraction to the palm or proximal interphalangeal joint is very rare. We present a case of type IV injury in a 45-year-old man with a pulling-on injury. The repair followed a pull-out technique (reinserting the tendon into the avulsed fragment); the entire reduction was tied over a button on the dorsal aspect of the nail and was augmented with a volar plate. The case was reported due to its rarity. We found that early surgical management of this problem greatly

Background: Swine influenza (also Called pig influenza, swine flu, hog flu and pig flu) is an infection by any one of several types of swine influenza virus (SIV) or S-OIV (Swine-Origin influenza virus) is any strain of the influenza family of viruses that is endemic in pigs. Patients and Methods:- Ninety patients with there families suspected of swine flu who were admitted to Central Teaching Hospital of Pediatric in Baghdad seventy one from Baghdad Al-Kerkh, twelve from Baghdad Al-Rasafa and seven other Iraqi Governorate (1 in Suleimaniya, 2 in Baquba, 4 in Anbar) they were included in a prospective study started from the 1st October till the 30 th of November 2009. Results:- The study revealed from )90( suspected cases the H1N1 Virus Pos

The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detec

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant