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Detecting intrusion in network traffic has remained a problem for years. Development in the field of machine learning provides an opportunity for researchers to detect network intrusion without using a database signature. Accuracy and completeness are two critical aspects in determining the performance of an intrusion detection system. The amount of unbalanced training data on each type of attack causes the system to have high accuracy, but it is difficult to detect all kinds of attacks. So, it does not meet the completeness aspect. In this paper, we propose an intrusion detection model using a combination of the modified rank-based information gain feature selection method, log normalization, and Support Vector Machine with parameter optimization. Overall accuracy achieved using 17 features from NSLKDD dataset is 99.8%, while the false alarm rate is 0.2%. The completeness aspect can be achieved, and the detection accuracy of the minority class can be increased.

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Objective: This study aimed to elucidate whether inhalation particulate matter 10 (PM10) of coal dust changes mesostructure, bone mineral elements, and turnover markers of rats. Methods: Thirty-two male Wistar rats were randomly divided into four groups; one non-inhaled group and three coal dust exposed groups (concentration 6.25, 12.5, and 25 mg/m3/h/day for 28 days). Femur mesostructure were analyzed by scanning electron microscope. Bone mineral elements was assayed by X-ray fluorescence. Osteocalcin and C-telopeptide of type I collagen were analyzed by ELISA. ANOVA test was used to analyze the difference level of all markers. Results: Mesostructure of non-inhaled rats presented rod like trabeculae with honey comb appearance and minimal hole. Disregular integrity of trabeculae and reduction of trabecular integrity, increasing porocity were found at coal dust exposed groups. The level of osteocalcin and C-telopeptide of type I collagen were significantly lower in coal dust exposed groups compared to control group. The levels of phosphorus and nickel were significantly lower in coal dust exposed groups compared to control group. Conclusion: The present study reported that sub-chronic inhalation of coal dust PM10 changes bone mesostructure, phosporus and nickel levels in bone, and bone turnover markers of rats’ femur. [J Exp Integr Med 2013; 3(2.000): 153-158