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BACKGROUND The present study aimed to investigate the characteristics of occupational accidents and frequency and severity of work related accidents in the construction industry among Iranian insured workers during the years 20072011. METHODS The Iranian Social Security Organization (ISSO) accident database containing 21,864 cases between the years(More)
Due to a growing number of the computer networks in recent years, there has been an increasing interest in the intrusion detection systems (IDSs). In this paper we have proposed a method applied to the instance selection from KDD CUP 99 dataset which is used for evaluating the anomaly detection techniques. In order to determine the performance of proposed(More)
Face recognition systems due to their significant application in the security scopes, have been of great importance in recent years. The existence of an exact balance between the computing cost, robustness and their ability for face recognition is an important characteristic for such systems. Besides, trying to design the systems performing under different(More)
A Bayesian classifier is one of the most widely used classifiers which possess several properties that make it surprisingly useful and accurate. It is illustrated that performance of Bayesian learning in some cases is comparable with neural networks and decision trees. Bayesian theorem suggests a straight forward process which is not based on search(More)
Accidents involving falls and falling objects (group I) are highly frequent accidents in the construction industry. While being hit by a vehicle, electric shock, collapse in the excavation and fire or explosion accidents (group II) are much less frequent, they make up a considerable proportion of severe accidents. In this study, multiple-correspondence(More)
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